Google rapidly expanded AI Overviews in search during 2025, then pulled back as they moved into commercial and navigational queries. These findings are based on a new Semrush analysis of more than 10 million keywords from January to November.
AI Overviews surged, then retreated. Google didn’t roll out AI Overviews in a straight line in 2025. A mid-year spike gave way to a pullback, suggesting Google moved fast to test the feature, then eased off based on user data:
January: 6.5% of queries triggered an AI Overview
July: AI Overview visibility peaked, appearing in just under 25% of queries.
November: Coverage fell back to less than 16% of queries.
Zero-click behavior defied expectations. Surprisingly, click-through rates for keywords with AI Overviews have steadily risen since January. AI Overviews don’t automatically reduce clicks and may even encourage them.
AI Overviews still appear more often on searches that already tend to drive no clicks.
But when Semrush compared the same keywords before and after an AI Overview appeared, zero-click rates fell from 33.75% to 31.53%.
Informational queries no longer dominate. Early 2025 AI Overviews were almost entirely informational:
January: 91% informational
October: 57% informational
Now, AI Overviews are appearing for commercial and transactional queries:
Commercial queries: Increased from 8% to 18%
Transactional queries: Increased from 2% to 14%
Navigational queries are rising fast. In an unexpected shift, AI summaries are increasingly intercepting brand and destination searches:
Navigational AI Overviews grew from under 1% in January to more than 10% by November.
Google Ads + AI Overviews. Earlier this year, ads rarely appeared next to AI Overviews. Now they’re common:
Ads alongside AI Overviews rose from about 3% in January to roughly 40% by November.
Ads show at the bottom of around 25% of AI Overview SERPs.
Science is the most impacted industry. By keyword saturation, Science leads all verticals for AI Overviews at 25.96%. Computers & Electronics follows at 17.92%, with People & Society close behind at 17.29%.
Since March, Food & Drink has seen the fastest growth in AI Overviews of any category.
Meanwhile, Real Estate, Shopping, and Arts & Entertainment remain lightly affected, with AI Overviews appearing on fewer than 3% of keywords.
Why we care. AI Overviews are unevenly and persistently reshaping click behavior, commercial visibility, and ad placement. Volatility is likely to continue, so closely monitor performance shifts tied to AI Overviews.
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Google’s pitch for AI-powered bidding is seductive.
Feed the algorithm your conversion data, set a target, and let it optimize your campaigns while you focus on strategy.
Machine learning will handle the rest.
What Google doesn’t emphasize is that its algorithms optimize for Google’s goals, not necessarily yours.
In 2026, as Smart Bidding becomes more opaque and Performance Max absorbs more campaign types, knowing when to guide the algorithm – and when to override it – has become a defining skill that separates average PPC managers from exceptional ones.
AI bidding can deliver spectacular results, but it can also quietly destroy profitable campaigns by chasing volume at the expense of efficiency.
The difference is not the technology. It is knowing when the algorithm needs direction, tighter constraints, or a full override.
This article explains:
How AI bidding actually works.
The warning signs that it is failing.
The strategic intervention points where human judgment still outperforms machine learning.
How AI bidding actually works – and what Google doesn’t tell you
Smart Bidding comes in several strategies, including:
Each uses machine learning to predict the likelihood of a conversion and adjust bids in real time based on contextual signals.
The algorithm analyzes hundreds of signals at auction time, such as:
Device type.
Location.
Time of day.
Browser.
Operating system.
Audience membership.
Remarketing lists.
Past site interactions.
Search query.
It compares these signals with historical conversion data to calculate an optimal bid for each auction.
During the “learning period,” typically seven to 14 days, the algorithm explores the bid landscape, testing bid levels to understand the conversion probability curve.
Google recommends patience during this phase, and in general, that advice holds. The algorithm needs data.
The first problem is that learning periods are not always temporary.
Some campaigns get stuck in perpetual learning and never achieve stable performance.
Google’s optimization goals vs. your business goals
The algorithm optimizes for metrics that drive Google’s revenue, not necessarily your profitability.
When a Target ROAS of 400% is set, the algorithm interprets that as “maximize total conversion value while maintaining a 400% average ROAS.”
Notice the word “maximize.”
The system is designed to spend the full budget and, ideally, encourage increases over time.
More spend means more revenue for Google.
Business goals are often different.
You may want a 400% ROAS with a specific volume threshold.
You may need to maintain margin requirements that vary by product line.
Or you may prefer a 500% ROAS at lower volume because fulfillment capacity is constrained.
The algorithm does not understand this context.
It sees a ROAS target and optimizes accordingly, often pushing volume at the expense of efficiency once the target is reached.
This pattern is common. An algorithm increases spend by 40% to deliver 15% more conversions at the target ROAS. Technically, it succeeds.
In practice, cash flow cannot support the higher ad spend, even at the same efficiency.
The algorithm does not account for working capital constraints.
Key signals the algorithm can’t understand
AI bidding works well, but it has limits.
Without intervention, several factors can’t be fully accounted for.
Seasonal patterns not yet reflected in historical data
Launch a campaign in October, and the algorithm has no visibility into a December peak season.
It optimizes based on October performance until December data proves otherwise, often missing early seasonal demand.
Product margin differences
A $100 sale of Product A with a 60% margin and a $100 sale of Product B with a 15% margin look identical to the algorithm.
Both register as $100 conversions. The business impact, however, is very different.
This is where profit tracking, profit bidding, and margin-based segmentation matter.
Customer lifetime value variations
Unless lifetime value modeling is explicitly built into conversion values, the algorithm treats a first-time customer the same as a repeat buyer.
In most accounts, that modeling does not exist.
Market and competitive changes
When a competitor launches an aggressive promotion or a new entrant appears, the algorithm continues bidding based on historical conditions until performance degrades enough to force adjustment.
Market share is often lost during that lag.
Inventory and supply chain constraints
If a best-selling product is out of stock for two weeks, the algorithm may continue bidding aggressively on related searches because of past performance.
The result is paid traffic that cannot convert.
This is not a criticism of the technology. It’s a reminder that the algorithm optimizes only within the data and parameters provided.
When those inputs fail to reflect business reality, optimization may be mathematically correct but strategically wrong.
Warning signs your AI bidding strategy is failing
The perpetual learning phase
Learning periods are normal. Extended learning periods are red flags.
If your campaign shows a “Learning” status for more than two weeks, something is broken.
Common causes include:
Insufficient conversion volume – the algorithm typically needs at least 30 to 50 conversions per month.
Frequent changes that reset the learning period.
Unstable performance with wide day-to-day fluctuations.
When to intervene
If learning extends beyond three weeks, either:
Increase the budget to accelerate data collection.
Loosen the target to allow more conversions.
Or switch to a less aggressive bid strategy like Enhanced CPC.
Sometimes the algorithm is simply telling you it does not have enough data to succeed.
Budget pacing issues
Healthy AI bidding campaigns show relatively smooth budget pacing.
Daily spend fluctuates, but it stays within reasonable bounds.
Problematic patterns include:
Front-loaded spending – 80% of the daily budget gone by 10 a.m.
Consistent underspending, such as averaging 60% of budget per day.
Volatile day-to-day swings, like spending $800 one day, $200 the next, then $650 after that.
Budget pacing is a proxy for algorithm confidence.
Smooth pacing suggests the system understands your conversion landscape.
Erratic pacing usually means it is guessing.
The efficiency cliff
This is the most dangerous pattern. Performance starts strong, then gradually or suddenly deteriorates.
This shows up often in Target ROAS campaigns.
Month 1: 450% ROAS, excellent.
Month 2: 420%, still good.
Month 3: 380%, concerning.
Month 4: 310%, alarm bells.
What happened?
The algorithm exhausted the most efficient audience segments and search terms.
To keep growing volume – because it is designed to maximize – it expanded into less qualified traffic.
Broad match reached further. Audiences widened. Bid efficiency declined.
Traffic quality deterioration
Sometimes the numbers look fine, but qualitative signals tell a different story.
Engagement declines – bounce rate rises, time on site falls, pages per session drop.
Geographic shifts appear as the algorithm drives traffic from lower-value regions.
Device mix changes, often skewing toward mobile because CPCs are cheaper, even when desktop converts better.
Time-of-day misalignment can also emerge, with traffic arriving when sales teams are unavailable.
These quality signals do not directly influence optimization because they are not part of the conversion data.
To address them, the algorithm needs constraints: bid adjustments, audience exclusions, or ad scheduling.
The search terms report reveals the truth
The search terms report is the truth serum for AI bidding performance.
Export it regularly and look for:
Low-intent queries receiving aggressive bids.
Informational searches mixed with transactional ones.
Irrelevant expansions where the algorithm chased conversions into entirely different intent.
A high-end furniture retailer should not spend $8 per click on “free furniture donation pickup.”
A B2B software company targeting “project management software” should not appear for “project manager jobs.”
These situations occur when the algorithm operates without constraints.
Keyword matching is also looser than it was in the past, which means even small gaps can allow the system to bid on queries you never intended to target.
Strategic intervention points: When and how to take control
Segmentation for better control
One-size-fits-all AI bidding breaks down when a business has diverse economics.
The solution is segmentation, so each algorithm optimizes toward a clear, coherent goal.
Separate high-margin products – 40%+ margin – into one campaign with more aggressive ROAS targets, and low-margin products – 10% to 15% margin – into another with more conservative targets.
If the Northeast region delivers 450% ROAS while the Southeast delivers 250%, separate them.
Brand campaigns operate under fundamentally different economics than nonbrand campaigns, so optimizing both with the same algorithm and target rarely makes sense.
Segmentation gives each algorithm a clear mission. Better focus leads to better results.
Bid strategy layering
Pure automation is not always the answer.
In many cases, hybrid approaches deliver better results.
Run Target ROAS at 400% under normal conditions, then manually lower it to 300% during peak season to capture more volume when demand is high.
Use Maximize Conversion Value with a bid cap if unit economics cannot support bids above $12.
Group related campaigns under a portfolio Target ROAS strategy so the algorithm can optimize across them.
For campaigns with limited conversion data or volatile performance, Enhanced CPC offers algorithmic assistance without full black box automation.
The hybrid approach
The most effective setups combine AI bidding with manual control campaigns.
Allocate 70% of the budget to AI bidding campaigns, such as Target ROAS or Maximize Conversion Value, and 30% to Enhanced CPC or manual CPC campaigns.
Manual campaigns act as a baseline. If AI underperforms manual by more than 20% after 90 days, the algorithm is not working for the business.
Use tightly controlled manual campaigns to capture the most valuable traffic – brand terms and high-intent keywords – while AI campaigns handle broader prospecting and discovery.
This approach protects the core business while still exploring growth opportunities.
COGS and cart data reporting (plus profit optimization beta)
Google now allows advertisers to report cost of goods sold, or COGS, and detailed cart data alongside conversions.
This is not about bidding yet, but seeing true profitability inside Google Ads reporting.
Most accounts optimize for revenue, or ROAS, not profit.
A $100 sale with $80 in COGS is very different from a $100 sale with $20 in COGS, but standard reporting treats them the same.
With COGS reporting in place, actual profit becomes visible, dramatically improving the quality of performance analysis.
To set it up, conversions must include cart-level parameters added to existing tracking.
These typically include item ID, item name, quantity, price, and, critically, the cost_of_goods_sold parameter for each product.
Access is limited, but advertisers with clean COGS data flowing into Google Ads can request entry.
In this model, bids are optimized around actual profit margins rather than raw conversion value.
This is especially powerful for retailers with wide margin variation across products.
For advertisers without access to the beta, a custom margin-tracking pixel can be implemented manually. It is more technical to set up, but it achieves the same outcome.
AI bidding works best when the fundamentals are in place:
Sufficient conversion volume.
A stable business model with consistent margins and predictable seasonality.
Clean conversion tracking.
Enough historical data to support learning.
In these conditions, AI bidding often outperforms manual management by processing more signals and making more granular optimizations than humans can execute at scale.
This tends to be true in:
Mature ecommerce accounts.
Lead generation programs with consistent lead values.
SaaS models with predictable trial-to-paid conversion paths.
When those conditions hold, the role shifts.
Bid management gives way to strategic oversight – monitoring trends, identifying expansion opportunities, and testing new structures.
The algorithm then handles tactical optimization.
Preparing for AI-first advertising
Google is steadily reducing advertiser control under the banner of automation.
Performance Max has absorbed Smart Shopping and Local campaigns.
Asset groups replace ad groups.
Broad match becomes mandatory in more contexts.
Negative keywords increasingly function as suggestions the system may or may not honor.
For advertisers with complex business models or specific strategic goals, this loss of granularity creates tension.
You are often asked to trust the algorithm even when business context suggests a different decision.
That shift changes the role. You are no longer a bid manager.
You are an AI strategy director who:
Defines objectives.
Provides business context.
Sets constraints.
Monitors outcomes.
Intervenes when the system drifts away from strategic intent.
No matter how advanced AI bidding becomes, certain decisions still require human judgment.
Strategic positioning – which markets to enter and which product lines to emphasize – cannot be automated.
Neither can creative testing, competitive intelligence, or operational realities like inventory constraints, margin requirements, and broader business priorities.
This is not a story of humans versus AI. It is humans directing AI.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/12/When-Googles-AI-bidding-breaks-E28093-and-how-to-take-control-9Z1HvO.jpg?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-16 15:00:002025-12-16 15:00:00When Google’s AI bidding breaks – and how to take control
Shopify powers more than 6 million live ecommerce websites, supported by a robust app ecosystem that can extend nearly every part of the customer journey.
Anyone can develop an app to perform virtually any function.
But with so many integrations to choose from, ecommerce teams often waste time testing add-ons that promise revenue gains but fail to deliver.
Having worked across a wide range of Shopify implementations, I’ve seen which tools consistently improve checkout completion, recover abandoned carts, and increase revenue.
Based on that experience, I’ve organized the most effective integrations into three tiers by priority – so you can implement the essentials first, then move on to more advanced optimization.
As a result, every Shopify site should have two components integrated into its storefront:
A digital wallet compatibility.
A buy now, pay later (BNPL) option.
Without these in place, Shopify users introduce unnecessary friction into the purchase journey and risk sending customers to competitors.
The good news is that both components integrate natively with Shopify, requiring no custom development.
Why you need digital wallets
Digital wallets, such as Apple Pay, Google Pay, and PayPal, autofill delivery and payment information with a single click, eliminating the friction of typing on a small screen.
This ease of use can shorten the purchase journey to just a few clicks between a social ad and checkout.
Adoption is accelerating. Up to 64% of Americans use digital wallets at least as often as traditional payment methods, and 54% use them more often.
Eliminate price objections with BNPL
Beyond payment convenience, customers also expect flexibility.
BNPL providers, including Klarna and Afterpay, allow buyers to spread payments over time, reducing price objections at checkout.
These options contributed $18.2 billion to online spending during last year’s holiday season – an all-time high, according to Adobe.
Together, digital wallets and BNPL form the foundation of a modern, mobile-first checkout experience.
With these essentials in place, Shopify users can focus on tools that re-engage customers and bring them back to complete their purchases.
The second tier focuses on re-engagement – tools designed to bring back customers who have already shown intent.
These integrations improve abandoned-cart recovery, increase repeat purchases, and build trust through social proof.
Re-engage customers with email and SMS
Email remains one of the most effective channels for re-engaging customers at every stage of the journey.
Klaviyo and Attentive are strong options for Shopify users because both offer deep platform integration with minimal setup.
Both platforms also support SMS, allowing Shopify sellers to send automated text messages directly to customers’ mobile devices.
SMS consistently delivers higher open, click-through, and conversion rates than email, making it especially effective for re-engagement use cases such as abandoned-cart recovery.
Together, these tools enable targeted campaigns and sophisticated automated flows that drive incremental revenue.
However, CAN-SPAM and TCPA regulations require explicit opt-in for email and SMS marketing, respectively.
As a result, sellers can only use these channels to contact customers who have agreed to receive marketing messages.
Use human-centered SMS outreach
While Attentive and Klaviyo effectively reach customers who have opted in to marketing, CartConvert helps sellers engage the 50% to 60% of shoppers who have not.
The platform uses real people to contact cart abandoners via SMS. Because the outreach is not automated, TCPA restrictions do not apply.
CartConvert agents have live conversations with potential customers about their shopping experience.
They are familiar with the products and can guide buyers back toward a purchase by suggesting alternatives or offering discounts.
Running CartConvert alongside Klaviyo or Attentive ensures both subscribers and non-subscribers are included in re-engagement efforts.
Human-centered marketing also plays a role in building buyer confidence.
Today’s online shoppers rely heavily on reviews when making purchasing decisions.
When reviews are integrated directly into the shopping experience, they help establish trust and legitimacy, which in turn drive higher conversion rates.
A product with five reviews is 270% more likely to be purchased than one with no reviews, research from the Spiegel Research Center at Northwestern University found.
Shopify users can choose from several review aggregators that pull Google reviews into product pages.
Sellers should prioritize aggregators that also sync with Google Merchant Center, which powers Google Ads.
Tools such as Okendo, Yotpo, and Shopper Approved integrate smoothly with both Shopify and Google’s ecosystem.
When reviews sync with Merchant Center, they can appear in Google Shopping ads, improving ad performance.
While these tools add cost, they are also proven to generate incremental revenue that offsets the investment.
The final tier includes more advanced integrations designed to help sellers optimize their sales funnel and performance at scale.
Attribution and analytics: Triple Whale
GA4’s changes to reporting, session logic, and interface have made attribution more difficult for many ecommerce teams.
As a result, sellers are increasingly seeking clearer, independent performance insights.
Since 2023, Triple Whale has emerged as a leading alternative to Google Analytics, offering third-party attribution tools that integrate seamlessly with Shopify.
The platform supports multiple attribution models – including first-click, last-click, and linear – along with cross-platform cost integration.
It also provides real-time data, which Google Analytics does not.
This capability becomes especially valuable during high-pressure sales periods, such as Black Friday, when delayed reporting can lead to missed opportunities.
Although Triple Whale can cost up to $10,000 annually for mid-size brands, the improved data quality often justifies the investment for teams scaling paid acquisition.
Landing page customization: Replo
For sellers focused on improving conversion rates, landing page testing is essential.
While Shopify is relatively easy to use, making changes to a live storefront for A/B testing carries the risk of breaking the site.
Replo allows Shopify users to build custom landing pages that can be tested at scale without coding.
These pages typically provide a better user experience than default Shopify themes.
It can also use site data to personalize landing pages based on a shopper’s browsing history.
As a result, Replo-built pages often convert at higher rates than static site pages.
TikTok ads integration
TikTok continues to grow as a paid media channel, but it has traditionally presented a higher barrier to entry for advertisers.
Previously, sellers needed an active TikTok account and could only purchase ads within the app, adding complexity and cost.
TikTok’s Shopify integration allows sellers to create ads that link directly to their websites, rather than keeping users inside the app.
This change has lowered the barrier to entry and expanded access to the platform.
Early testing shows promise for use cases such as cart abandonment, making the integration worth exploring despite its relative immaturity.
Prioritizing Shopify integrations for maximum impact
Shopify is a powerful platform for ecommerce, but maximizing results requires going beyond its default features.
Start with essentials such as digital wallets and BNPL to reduce checkout friction.
Then layer in email, SMS, and review integrations to re-engage interested shoppers.
Finally, add analytics, attribution, and landing-page testing to optimize performance at scale.
Sellers do not need to implement every solution at once.
Instead, conduct a quick audit of the existing stack against this framework, identify gaps, and prioritize the tools that improve conversion and re-engagement.
Shopify’s flexibility is its greatest strength, and its app ecosystem enables sellers to turn more visitors into buyers.
Managing large catalogs in Google Performance Max can feel like handing the algorithm your wallet and hoping for the best.
La Maison Simons faced that exact challenge: too many products and not enough control. Then they rebuilt their segmentation with Channable Insights and turned a “black box” campaign into a revenue-generating machine.
Step 1: Stop segmenting by category
Simons originally split campaigns by product category. It sounded logical – until their best-selling sweater ate the budget and newer or overlooked products never had a chance to surface.
Static segmentation meant limited visibility and slow decisions.
Marketers stayed stuck making manual tweaks while Google kept auto-prioritizing only what was already working.
Step 2: Segment by performance
Enter Channable Insights. Product-level performance data (ROAS, clicks, visibility) now powers dynamic grouping:
Products automatically move between these segments as performance shifts – no manual work needed. As Etienne Jacques, Digital Campaign Manager, Simons, put it:
“One super popular item no longer takes all the money.”
Step 3: Shorten your analysis window
Instead of waiting 30 days for signals, Simons switched to a rolling 14-day window.
The result: faster reactions, sharper accuracy, and less wasted spend in a fast-moving catalog.
Step 4: Push the strategy across channels
Why stop at Google? The same segmentation logic was automatically applied on:
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/12/Channable-SEL-Sponsored-Post-Feature-Image-Final-pgWBTD.webp?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-16 12:00:002025-12-16 12:00:00How to boost ROAS like La Maison Simons by Channable
Google Ads launched VTC-optimized bidding for Android app campaigns, letting advertisers toggle bidding toward conversions that happen after an ad is viewed rather than clicked.
Previously, VTC worked as a hidden signal inside Google’s systems. Now, it’s a clear, explicit optimization option.
Reddit is an online forum that’s part search engine, part social network.
Millions of people use it to swap advice, review products, and argue about virtually every topic under the sun. It all happens inside niche communities called subreddits.
All this makes it a powerful place for Reddit marketing. As long as you know how to play by its rules, that is.
The No. 1 rule? You can’t treat Reddit like another broadcast channel. Users hate obvious self-promotion and call out spam instantly. They reward brands that show up to add value, so just popping in and dropping links won’t cut it.
The upside? If you’re useful and authentic, the reward is real trust and traffic you won’t get anywhere else.
In this guide, we’ll walk you through how to market on Reddit the right way, including both organic and paid strategies. We’ll also toss in some tips on etiquette to keep you from getting buried (or banned).
Key Takeaways
Reddit is a network of niche communities. Winning here means respecting each sub’s rules and culture.
Organic comes first. Use a Crawl-Walk-Run approach in your Reddit marketing strategy: Listen and comment, then start useful threads, then scale into branded subs, SEO plays, and selective paid campaigns.
Self-promotion is allowed but heavily policed. Contribute more than you pitch and follow Reddiquette and subreddit rules to avoid bans and backlash.
Reddit ads run on an auction model and work best when they feel native to the feed.
Reddit threads influence Google results, “Discussions and forums” boxes, and even AI answers.
Why Is Reddit Important as a Marketing Platform?
Reddit is massive and growing fast. Recent estimates put it at around 100 million daily active users and hundreds of millions of monthly users, spread across more than 100,000 active subreddits.
It’s basically a giant ecosystem of niche communities where people compare products, troubleshoot problems, and share unfiltered opinions.
What makes Reddit especially relevant today is how often its content shows up outside Reddit. Google’s “Discussions and forums” search feature appears on millions of queries and is heavily dominated by Reddit threads, especially for product reviews and how-to topics.
Check out the “Discussions and forums” results for “best VPN for travel.” Reddit grabs the top spot above Facebook groups, which tells you two things: Google trusts Reddit threads for experience-based queries, and real travelers would rather hear from other travelers than from brand pages.
When someone searches “running shoes for bad knees,” for example, a Reddit discussion appears on page one.
“Google, specifically, is prioritizing the platform because it highlights true first-hand experiences,” says Becky McManus, senior SEO strategist at NP Digital.
Reddit’s also a growing force in AI search. It has data-licensing deals with Google and OpenAI, which use Reddit posts to train and power their large language models. In some analyses, Reddit is one of the most commonly cited domains in AI-generated answers.
So, when you show up on Reddit, you’re not just reaching users on one platform. You’re influencing search results, AI-generated summaries, and the conversations that shape buyer decisions.
Fundamentals to Know About Reddit
Maybe the most fundamental thing to know about Reddit is that it isn’t one big audience. It’s a web of niche communities (subreddits). Each has its own rules and culture. And not all of them have a high tolerance for brands.
“Reddit is a different kind of digital marketing space,” McManus says. “It’s all about being real and adding value to the conversation, not just pushing promotions, which you can do more of on standard social media platforms.”
That’s what makes Reddit marketing powerful. It’s also what makes it easy to screw up.
Start with the basics by reading Reddit’s page about self-promotion and what’s allowed and what isn’t. Once you’ve read that, look at the “Reddiquette” page so you can see Reddit’s main rules.
The list includes:
Contributing more than you promote and avoiding spammy, link-only posts
Being transparent about who you are and any affiliations you have
Speaking to other users respectfully, even when you disagree
Following each subreddit’s specific rules instead of assuming they’re all the same
Next, zoom in on each subreddit.
Read the sidebar and pinned posts. Some communities allow links only on certain days. Others ban surveys, coupon codes, or branded content of any kind. Moderators (mods) enforce those rules, and they won’t hesitate to remove posts or ban accounts.
Take a look at how the r/digitalmarketing subreddit clearly spells out its rules.
Your job is to show up as a helpful user first and a marketer second. Answer questions, share experiences, post useful resources, and only occasionally mention your product when it genuinely fits the thread.
If you’re unsure whether something crosses the line, message the mods and ask.
Organic Reddit Strategies
Organic participation is the name of the game withReddit marketing.
Ads can help, but many brands win by showing up as real users first. That means answering questions and sharing useful resources, which helps build karma over time.
Done right, this also feeds into your Reddit SEO strategy before you ever touch paid campaigns.
Use a Business Account
If you’re going to do anything promotional on Reddit, start with a branded account. Redditors care a lot about transparency, and a handle that clearly represents your company or team builds more trust than a random personal username that secretly belongs to “Marketing.”
Create an account that signals who you are (for example, BrandName_Official or FirstNameAtBrand). Add a short bio that explains your role and what people can expect from you, such as support or product questions.
Here’s an example profile from Cleveland.com, whose parent company, Advance Local, has had success with organic Reddit marketing strategies.
From there, resist the urge to start dropping links. Instead, comment, answer questions, and join existing threads. That way, your profile doesn’t look like it was created only to push content. If teammates also use personal accounts, have them be open about their affiliation when it’s relevant.
An honest business presence boosts the credibility of every future promo. It also looks less like spam.
Provide Value to Communities
Reddit rewards accounts that make threads better. If your first instinct is “Where can I post my link?”, you’re already in trouble.
Focus on being useful long before you mention your brand.
Look for questions you can answer in detail. Share things like:
How-tos
Real examples
What actually worked for you, even when the answer doesn’t involve your product.
Summarize complex topics in plain language.
Drop frameworks, checklists, or quick diagnostics people can try on their own.
You can also add value by recapping good resources, explaining trade-offs between options, or sharing honest pros and cons from your experience. Link sparingly and only when it clearly adds context.
Over time, that kind of participation builds karma, name recognition, and trust. Then, when you occasionally share something from your own site, it feels like a contribution, not an intrusion.
Ask Me Anything (AMA)
AMAs can be useful, even if you’re not a household name. The key is to find a clear, interesting angle that fits the subreddit.
Instead of “I’m a founder; ask me anything,” pitch something specific to the mods first:
“I run growth for a bootstrapped SaaS that just hit $1M ARR. Ask me anything about what actually moved the needle.”
“I’ve moderated a 200K-member fitness community for five years. Ask me anything about what keeps people engaged.”
For example, this AMA works because it leads with a high-stakes, personal hook: someone risking their life savings on a mobile game. People want to hear the story and ask what happened next.
Most subreddits require proof and mod approval, so follow their instructions closely. During the AMA, focus on being candid and helpful. Share stories, mistakes, and lessons. Avoid turning every answer into a soft pitch.
If people like you, they’ll click through to your profile and brand on their own. The AMA’s job is to build credibility, not to read like a live ad.
Start a Subreddit
Starting your own subreddit is more of a “phase two or three” move than a starting point. If you don’t already have people talking about you on Reddit, a brand-new sub will sit empty and make you look inactive.
Once there’s clear interest—mentions in other subs, recurring questions, or an existing community elsewhere—you can launch a subreddit as a hub. Think of it as a place for support, feature requests, user wins, and deeper discussions around your niche, not just announcements.
Set clear rules, pin a simple “Start here” post, and seed the sub with genuinely useful threads: FAQs, guides, templates, product walkthroughs, or office-hours posts. Commit to moderating and replying.
When you promote the subreddit, invite people in for the value (“Come ask questions and see real use cases”), not just to “follow” your brand.
Reddit Paid Advertising
Organic participation is the foundation of your Reddit marketing efforts, but paid ads are how you scale once you know what resonates.
Reddit now reaches a massive, mostly younger audience across thousands of active communities, and a lot of those users are actively researching products (not just scrolling).
The big advantage for marketers is context.
You can target by subreddit, interest, keyword, location, and device, so your ads show up inside conversations that already match your offer. Formats range from promoted posts and video ads to conversation placements and takeovers, with newer options like dynamic product ads for e-commerce.
If your creative matches the culture of the communities you’re in, Reddit ads can drive serious awareness and consideration.
Reddit Advertising Policies
Reddit’s ad policies are strict because ads sit right next to user posts. If your campaigns feel spammy or misleading, you’d better believe they’ll get rejected fast. Even when they’re approved, users will downvote them into oblivion.
Creative and Video Quality
Ads should look and sound professional. Make sure your audio and visuals are clear and text is readable.
Also be sure your video is relevant to the audience you’re targeting and correctly labeled if it includes mature themes. Anything graphic or heavily profane needs the proper rating and warnings, and strobing or flashing effects are off limits.
Style and Copy Standards
Reddit expects clean, honest copy. So, check your spelling and grammar, keep emojis and symbols to a minimum, avoid shouty all-caps, and don’t stuff personal data into your ad unless regulations require it. And be sure that your images are high quality and match what you’re promoting.
Accuracy and Transparency
Your ad has to reflect the real product or service. That means no clickbait headlines or no bait-and-switch offers. And don’t promote specific Reddit comments or posts unless you’re using approved formats.
URLs and Landing Pages
Your landing page should clearly feature the product you advertised. You’ll also want it to load reliably and stick to Reddit’s content rules. Keep the language consistent with your ad and avoid aggressive pop-ups or spammy tactics.
When in doubt, review Reddit’s full advertising policy before you launch. It’s easier to fix issues in draft than after a denial.
What Are the Different Types of Reddit Ads?
Reddit’s ad formats are designed to feel like part of the feed, not banner clutter. Here’s how the main options break down in Reddit’s own language:
Free-form ads: Reddit-native units that can mix text, images, video, and GIFs in one post. Great for storytelling or more complex messages.
Image ads: Single-image promoted posts that look like standard Reddit posts with a “Promoted” label. Solid for simple offers and clear CTAs.
Video ads: Autoplay video in the feed, built to grab attention and work across awareness, consideration, and conversion.
Carousel ads: Swipeable units that showcase multiple images or videos in one ad—perfect for product lines, before/after stories, or feature highlights.
Conversation ads: Let you join or spark discussions directly in conversation spaces, so your brand shows up where people are already talking.
Product ads: Shopping-focused units that pull from your product catalog and recommend items to redditors who are ready to buy.
AMA ads: Sponsored “ask me anything” experiences that put a subject-matter expert or brand rep at the center of a Q&A thread.
Most of these are available in the self-serve ads manager, so you can test formats quickly and double down on what your audience actually engages with.
Examples of Great Reddit Ads
Before diving and creating your own Reddit ad, let’s look at a few examples.
ChatGPT
This ad works because it feels like a Reddit post, not a banner. The headline clearly promises the benefit (“transform your words into works of art”), and the creative shows the product in action—a funny, hyper-specific dog portrait that fits Reddit’s meme-y culture.
The user interface screenshot makes it obvious how ChatGPT is used, so there’s no learning curve. The copy is light, the visual does the selling, and the single “Sign Up” call to action (CTA) keeps the next step simple.
All in all, it’s fun, clear, and native to the feed.
The Coupon Nerd
This ad works because it leans into Reddit’s strengths: story and specificity.
The headline (“I’m a massive savings nerd… stupidest money mistakes…”) sounds like a real thread you’d click, not brand copy. The post leads with concrete value—numbers, personal savings, and clear next steps—before it ever feels promotional.
It’s written in plain language, framed as advice from a fellow user, and backed by strong engagement (upvotes, comments), which signals social proof right in the feed.
How to Build Your Reddit Marketing Campaigns
Reddit doesn’t reward brands that rush in with a big ad budget. It rewards the ones that show up and learn the culture first.
That’s why it helps to think about Reddit marketing in stages instead of “launching a campaign” overnight.
Start with low-risk actions that teach you how each community works. Then layer on more visible content and light promotion. Once you know what lands, you can treat Reddit like a full channel.
In the sections below, we’ll walk through a practical Crawl → Walk → Run model you can use to move from basic participation to a scalable Reddit program that drives traffic and revenue (and not just karma).
Crawl
In the Crawl stage, your main job is to learn the ropes of Reddit and show up like a real user. You’ve set up a branded account, know the Reddiquette, and have your eyes on the subreddits where your audience already hangs out.
From here, keep it simple:
Read top and “hot” posts to get a feel for tone and what flies.
Comment on existing threads where you have real experience to share.
Answer questions in detail without instantly pushing your product.
Use Reddit search and “site:reddit.com” Google searches around your main topics to find the discussions that matter most to your buyers.
This screenshot shows the Crawl stage in action using a site search to see which subreddits and threads already rank for “gravel bikes.” It includes threads on clarifying the definition of a gravel bike and calls for product recommendations.
As you explore, pay attention to the phrases people use and the problems they describe. Also take note of the kind of answers they upvote.
Crawl is about listening and learning. You’re gathering intel on which communities are worth investing in. That way, you don’t sound like a marketer who just discovered Reddit yesterday.
Walk
In the Walk phase, you’re moving beyond “lurking” and turning your Reddit presence into a repeatable habit. Now, you’re showing up in a handful of high-value subreddits on purpose. You’re not just scrolling anymore.
Start by narrowing your focus. Pick three to five communities where your audience already hangs out and where you can add real expertise. Look for threads that match your core topics and keywords.
Your job at this stage is to:
Comment thoughtfully on existing threads, especially questions you can answer from experience.
Share occasional links to genuinely useful resources (yours or others), but always wrapped in context.
Track what gets upvotes, saves, and replies so you can see which angles resonate.
Think of Walk as your calibration stage. You’re learning the language and formats that work in each subreddit. You’re also starting to spot patterns you can later turn into content pillars, SEO topics, and even product ideas.
You’re not trying to dominate Reddit yet. You’re trying to become a familiar, helpful name in the spaces that matter.
“It’s all about trust,” says Becky McManus, the senior SEO strategist at NP Digital.
“Teams should expect to earn trust gradually by engaging authentically and consistently within the communities that genuinely care about what they offer.”
Run
Run is where Reddit becomes a proper channel, not just a side experiment.
By this point, you know:
Which subreddits respond best.
Which topics reliably spark quality discussion.
Which profiles (brand and team) have real credibility.
Now you can scale intentionally. This may include launching and actively moderating a branded subreddit as a hub for FAQs, feedback, updates, and success stories. You might also keep a presence in adjacent communities and jump into high-impact threads quickly.
From there, you can coordinate with your SEO and content teams to help keep responses and resources consistent.
Reddit becomes:
A content engine: Your best threads turn into blog posts, landing pages, videos, and email content.
An SEO asset: More of your conversations show up in SERPs and “Discussions and forums” modules.
A live focus group: You see unfiltered reactions to ideas, messaging, and features in real time.
At this stage, you can also layer in paid campaigns, but be sure to promote angles you already know resonate organically. That way, you’re not just guessing with ad dollars.
What Reddit Marketing Success Looks Like
A good example of Reddit done right is NP Digital’s work with TurboTax.
From January to April 2025, TurboTax-branded profiles joined relevant tax and personal finance threads, adding 159 thoughtful comments and starting targeted conversations during filing season.
The impact showed up well beyond Reddit. Several of those threads were pulled into Google’s “What people are saying” for searches like “quarterly tax deadlines” and “turbotax early refund,” and one comment was cited in AI-generated Reddit answers within days.
Brand mentions hit 5,404 (up 10 percent year over year), and positive mentions nudged up even in the middle of tough conversations about pricing and early refunds.
We also paired that Reddit work with SEO. A refreshed “Ways to File for Free” guide captured the featured snippet for “is turbotax free,” helping outrank older negative Reddit threads and giving TurboTax more control over how the brand shows up in search.
FAQs
How do you do marketing on Reddit?
Act like a helpful user, not a billboard: join relevant subreddits, add value in threads, then layer in carefully targeted information that can be tied back to your brand.
Can you self-promote on Reddit?
Yes, but only within strict limits. Reddit and most subreddits take a hard line on spammy self-promotion. If most of your activity is just dropping your own links, you’ll get downvoted or banned. Read Reddit’s self-promotion and Reddiquette guidelines and participate in conversations, but make sure any link you share is genuinely helpful and clearly relevant to the thread.
How do I create a Reddit marketing strategy?
Start with your goal (awareness, traffic, leads, or support), then map the subreddits your audience already uses. Create a branded account, learn each community’s rules, and spend time commenting before you post anything promotional. From there, plan a mix of organic participation (answers, explainers, AMAs, resource threads) and small paid tests once you know what resonates.
How do I market on Reddit without getting banned?
Read the FAQs, Reddiquette, and each subreddit’s rules before you start posting anything. And be sure to contribute more than you promote: answer questions, share experiences, and only link to your own content when it clearly adds value.
How much do Reddit ads cost?
Reddit ads run on an auction model, so prices vary widely. It sets its rates at $5 a day minimum, and costs vary from $1.50 to $10 per 1,000 impressions (or more for premium placements).
Conclusion
Reddit is a unique platform with millions of active users. It might seem like the ideal place to promote your business, but you could get banned (or ridiculed) if you aren’t careful.
Although Reddit is tougher on self-promotion on other platforms, that doesn’t mean marketers should steer clear of it altogether. Provided you stick to the rules and don’t stray into spamming or being “salesy,” you have the opportunity to grow a keen, engaged following.
Reddit can become one of your most valuable channels if you do it right. You can build trust inside niche communities, earn traffic from threads that rank in search, and even shape how your brand shows up in AI summaries.
With thousands of subreddits, there’s almost always a corner of Reddit where your audience is already talking. Show up to listen and answer questions as you learn the ropes.
Promotion comes later, after you’ve proven you’re there to add value, not just to cash in.
B2B marketing often gets treated like a second-class citizen compared to B2C. But here’s the truth: business-to-business marketing is growing fast and generating real results across industries.
Eighty percent of B2B buyers expect a B2C-like experience when interacting with brands. That means the old-school, relationship-only playbook won’t cut it anymore. You need a digital-first strategy that attracts high-quality leads, builds trust at scale, and drives measurable revenue.
In this guide, we’ll walk through proven B2B marketing strategies that actually work in 2026 and how to build your own roadmap from scratch.
Key Takeaways
B2B buyers are research-driven, digital-first, and selective.
Content marketing, SEO, and email are foundational for long-term growth.
LinkedIn and Google Ads are ideal for paid B2B campaigns.
You need a strategy built on your ideal customer profile, clear goals, and constant testing.
Trends like AI-generated content, video, and ABM are shaping the future of B2B digital marketing.
What is B2B Marketing?
B2B marketing stands for business-to-business marketing. Instead of selling directly to consumers (like B2C), you’re selling to other businesses.
That means longer sales cycles, more stakeholders, and a bigger focus on ROI. B2B decisions are driven by logic, not emotion. Buyers want to solve a pain point, improve operations, or generate a clear return.
In B2C, you might sell running shoes to a single customer. In B2B, you could be selling supply chain software to a procurement team of 12. That’s a very different game.
But even though you’re selling to companies, it’s still humans making the call. So your B2B strategy still needs to connect on a personal level.
How B2B Marketing Works Today
The modern B2B buyer looks a lot like a B2C consumer:
They start online.
They do extensive research.
They talk to peers.
They want to be educated before they talk to sales.
According to Gartner, 83% of a typical B2B purchasing decision happens before a buyer speaks with a sales rep. That means your marketing needs to do the heavy lifting.
The journey isn’t linear either. One stakeholder might download an e-book. Another might follow your brand on LinkedIn. A third might attend your webinar two months later. You need to stay visible and valuable at every stage.
Digital-first, multi-touch, always-on marketing wins in B2B today. It’s about building trust long before the sales team gets involved.
Core B2B Marketing Strategies That Work
There isn’t one silver bullet for B2B growth, but there are a handful of tried-and-true strategies that consistently deliver results. From attracting leads to nurturing them into customers, each of these plays a key role in your overall marketing mix.
Content Marketing
Content marketing is at the heart of every successful B2B strategy. It’s how you build authority, answer buyer questions, and stay visible throughout long sales cycles. Whether it’s blog posts, whitepapers, or customer success stories, great content gives prospects a reason to trust you before they buy.
Create a content calendar that includes top-of-funnel topics (like how-to posts or industry trends), mid-funnel pieces (case studies and solution guides), and bottom-funnel assets (ROI calculators, product comparisons). Use SEO research to guide your topics, and always write with your ICP’s pain points in mind. Update old content regularly to stay relevant, and use internal linking to guide users deeper into your funnel.
Blogs, whitepapers, guides, and case studies all play a role in educating and nurturing your audience. For example, security software provider Entrust does an annual report on fraud, relevant to their audience of enterprise, finance, and government professionals.
Long-form SEO-driven content builds authority and captures top-of-funnel traffic. Tie your strategy to the funnel. For example, TOFU is best suited for blogs, MOFU for case studies, and BOFU landing pages.
SEO
Search is where most B2B buyers begin. If you’re not showing up for high-intent keywords, you’re missing out on warm leads who are actively looking for a solution like yours. That’s why SEO is a non-negotiable for any serious B2B strategy.
Start by identifying search terms your audience uses throughout their buying journey through tools like Ubersuggest. Prioritize informational and commercial keywords, not just branded terms. Sometimes a low MSV may be okay if it’s relevant to your core audience, like the example below:
Optimize your site structure, title tags, meta descriptions and content. Build backlinks through guest posts and digital PR. Use schema markup to help search engines understand your pages. B2B SEO takes time, but it compounds, make it part of your long game.
Email Marketing
Email marketing continues to be the highest-performing B2B channel when it’s done right. It’s personal, direct, and measurable. But today’s buyers won’t tolerate one-size-fits-all blasts. You need segmentation, automation, and value in every send.
Use gated content and lead magnets to build your list, then segment it based on industry, buyer stage, or behavior. Set up automated drip campaigns that educate and nurture. Include useful resources, not just sales CTAs. Monitor open and click rates, and A/B test everything from subject lines to CTA placement. Good email marketing feels like a helpful nudge, not a pushy pitch.
Segment your lists by persona, behavior, and funnel stage. Use lead magnets like checklists or templates to grow your list. Automate nurture flows, and track opens, clicks, and replies.
Paid Ads
Organic takes time. Paid gives you speed and scale, especially when targeting high-value buyers. The key is precision. B2B paid ads work best when you combine targeting capabilities with smart messaging.
LinkedIn ads let you reach decision-makers by job title, industry, and company size. Google Search ads help you show up when someone searches for your product or service. Retarget website visitors with display or video ads to stay top of mind. Use UTM tracking to measure effectiveness, and continuously refine your copy and creatives. Paid ads work best when they amplify a strong organic strategy.
Webinars and Events
Webinars and virtual events are lead generation machines when done well. They give you the chance to educate prospects, show off your expertise, and interact with potential buyers in real time.
Pick topics that align with pain points your audience is actively researching. Bring in subject matter experts, use polls to engage viewers, and offer the replay as a gated asset post-event. Promote your webinar via email, social, and paid channels, especially after the initial release where it will show the most impact:
Events are also a content goldmine—turn recordings into short video clips, blog recaps, and nurture emails to extend their value.
They let you demonstrate expertise, answer objections, and collect leads. Keep topics specific. Invite prospects already in your pipeline. Repurpose the content as video clips, blog posts, or gated downloads.
B2B Vs B2C Marketing: How Do They Compare?
The biggest difference between B2B and B2C marketing comes down to the buyer’s mindset and how they make decisions.
Here’s a breakdown of how each approach typically differs:
B2B Marketing
Driven by ROI, efficiency, and logical outcomes
Longer sales cycles with multiple stakeholders
Higher-value deals and more complex products or services
Content is educational, technical, and data-backed
Messaging targets decision-makers and buying committees
B2C Marketing
Driven by emotion, desire, and personal benefit
Shorter sales cycles with individual decision-makers
Lower price points and more impulse-driven purchases
Content is entertaining, persuasive, and brand-oriented
Messaging targets individuals based on lifestyle or interests
These differences also extend to the type of content that performs well for each segment based on these needs.
How To Build a B2B Marketing Strategy From Scratch
You don’t need a huge team or budget to build a powerful B2B strategy. What you do need is clarity: on who you’re targeting, what you want to achieve, and how you’ll measure success. These are the building blocks every marketing plan should be built on.
Know Your Ideal Customer (ICP)
Everything starts with knowing who you’re selling to. Your ideal customer profile (ICP) should be specific and rooted in data—not assumptions. Outline key characteristics like industry, company size, annual revenue, and tech stack. Then go deeper: what roles make the buying decisions? What keeps them up at night? What objections do they raise in the sales process?
Use interviews, win/loss analysis, and CRM insights to map these out. A strong ICP informs your messaging, targeting, offers, and even product positioning. Without it, your marketing will feel generic—and miss the mark.
Who do you want to reach? What are their roles, pain points, objections, and decision criteria? Use interviews, surveys, and CRM data to build accurate personas.
Set Goals and KPIs
A marketing plan without measurable goals is just guesswork. Define success using metrics that align with business outcomes. Think beyond vanity metrics like impressions or traffic. Focus on KPIs such as MQLs, SQLs, CAC, CLV, and pipeline velocity.
Set benchmarks based on past performance or industry standards. Make sure sales and marketing agree on definitions and expectations. Use dashboards and regular reporting to track progress. When your team knows what “good” looks like, they’re more likely to hit it.
Track MQLs (marketing qualified leads), SQLs (sales qualified leads), CAC (customer acquisition cost), and CLV (customer lifetime value). Tie your KPIs to revenue.
Choose Your Channels
Don’t spread yourself thin trying to be everywhere. Choose marketing channels based on where your ICP actually spends time and how they make decisions.
LinkedIn is a powerhouse for targeting professionals. Email is ideal for nurturing. SEO brings long-term compounding returns. Paid ads provide immediate visibility. Webinars and events build authority. Select a mix of 2–4 core channels and go deep before you go wide.
Document how each channel maps to your funnel. Assign ownership and set clear goals for each.
Use a blend of organic and paid. For example: content + SEO + LinkedIn Ads.
Create a Content Plan
A content plan connects your ideas to outcomes. Start by mapping topics to each stage of the funnel: awareness, consideration, and decision. Awareness content (like blog posts) attracts traffic. Consideration content (like case studies or webinars) builds trust. Decision content (like pricing pages) removes friction.
Balance evergreen content that compounds over time with campaign-specific pieces tied to launches or seasonal priorities. Repurpose content across formats, turn webinars into blog posts, or blogs into LinkedIn posts. Make distribution part of the plan, not an afterthought.
Test and Optimize
No B2B strategy is perfect out of the gate. The best teams test constantly. Start with A/B tests on subject lines, CTAs, landing pages, and ad copy. Measure what actually moves the needle, not just what looks good.
Review performance weekly or monthly, depending on volume. Use heatmaps, CRM data, and attribution tools to identify where leads drop off. Small improvements add up fast, especially in long sales cycles. Optimization is where great marketing gets better.
A/B test CTAs, landing pages, ad creatives, subject lines. Run monthly reviews and adapt based on performance.
B2B Marketing Trends To Watch
Staying ahead in B2B marketing means paying attention to what’s gaining traction across digital channels.
AI Content Creation: Tools like ChatGPT, Jasper, and Writer.com are speeding up workflows and lowering content costs. That said, AI is best used for drafts, outlines, or ideation. Final outputs should still go through human editing to preserve quality, tone, and brand voice.
Video for Trust: Short-form video continues to dominate attention spans. Think beyond YouTube. Platforms like LinkedIn and TikTok now prioritize native video. B2B brands are using testimonial videos, product explainers, and founder messages to build credibility fast.
Account-Based Marketing (ABM): ABM is moving from enterprise-only to mid-market and even SMBs. With more tools available, it’s easier than ever to target specific accounts with personalized content, ads, and outreach. Align sales and marketing to increase close rates and shorten cycles.
First-Party Data Focus: With the decline of third-party cookies, companies are investing more in building their own data. Expect more gated content, newsletter offers, and community-building plays to capture emails and preferences directly from users.
Sales and Marketing Alignment: Marketing can no longer just focus on lead gen. It’s also about sales enablement, creating assets that help close deals. Look for tighter integration between CRM systems, shared KPIs, and ongoing collaboration between both teams.
Conversational Marketing: Chatbots and live chat are becoming standard on B2B websites. Instant answers and qualifications can speed up pipeline velocity. Use tools like Drift or Intercom to build conversational flows that feel personal, not robotic.
FAQs
What is B2B marketing?
B2B marketing stands for business-to-business marketing,strategies used to sell products or services to other businesses. B2B marketers use a mix of digital channels, from content, SEO, social media, email, PPC, and webinars to gain authority and interest from customers.
How do you do B2B marketing?
Build a strategy based on your ideal customer, set measurable goals, pick the right channels, and consistently test and improve.
How does content marketing help B2B?
Content builds trust and educates potential buyers before they talk to sales. It drives organic traffic and supports every stage of the funnel.
Conclusion
If you’re serious about growing in B2B, you need a digital strategy that reflects how modern buyers behave. They expect value at every interaction. They need proof that your solution works.
Focus on building trust through content, SEO, email, and targeted campaigns. Measure what matters. Optimize relentlessly.
And if you need help building a scalable, high-converting B2B strategy, NP Digital is here for you.
You’re investing in ads and other marketing strategies, but have you ever stopped to think about the data you’re using to inform those investments? For many companies, the biggest blind spot is tracking. Hidden misfires are skewing channel reporting and attribution, ultimately throwing off your marketing decisions.
At NP Digital, we’ve helped hundreds of clients uncover recurring patterns of tracking failure. Today, we’re sharing the most common issues we see and exactly how you can fix them. No fluff. Just real problems, real fixes, and proven next steps.
Key Takeaways
Attribution: Attribution bias is mitigated by using a shared taxonomy across data sources and maintaining clean first-party data.
GA4: Discrepancies around revenue and event tracking with business systems are solved by integrating GA4 data with those business systems.
Consent Management: Consent misconfigurations can lead to legal risk and lost data when CMPs are not mapped correctly to tag categories in the tag manager.
Cross-device: Use customer IDs to unify fragmented cross-device journeys.
Campaign Tracking: Custom setups need governance, so be sure to standardize campaign tracking structures, audit tags regularly, and align dashboards across marketing channels.
The Impact of Bad Data Tracking
Poor data tracking can be dangerous because it has the potential to distort every decision downstream. If your tags misfire, if a user doesn’t opt in and your scripts still run, or if your UTM query parameter structure breaks mid-campaign, you won’t know it until the numbers don’t add up. And by then, the damage is done.
We’ve seen firsthand how these silent issues erode marketing performance. The root causes usually fall into a few key categories:
Incomplete or incorrect tracking setups
Tracking that isn’t validated regularly
Misaligned naming conventions or taxonomies
And what happens when those issues go undetected?
Data gaps that make campaign comparisons impossible
Attribution errors that over-credit paid and undercount organic and vice-versa
Privacy violations if tags fire before consent, creating legal risk
Accurate tracking is the foundation of good marketing. And when it’s off, your strategy is too.
The Tracking Issues We See With Clients
Website tracking issues come in all shapes and sizes, but the same trends seem to emerge over the years of our experience working with clients. Across industries and platforms, we’ve found five tracking challenges that consistently disrupt clean data:
Broken or biased attribution
GA4 discrepancies.
Vendors restrict audience splits or don’t provide raw data
Algorithms self-optimize in ways that obscure true lift
Privacy-driven consent issues
Fragmented cross-platform journeys
Custom setups without a scalable structure
These issues don’t just mess with reporting, they impact performance and decision-making. In the next few sections, we’ll break down the causes of each issue and the solutions we provide to our clients.
Incrementality Measurement & Attribution Bias
Clients come to us with concerns about the accuracy of their reporting and questions on how they can determine what’s working/not working using their web analytics data. Once we dig into the attribution model, we realize it’s only telling half the story.
Attribution bias occurs when platforms over-credit or under-credit paid clicks and under or over-count the earlier part of the customer journey. Skewing the data this way creates inflated ROI on paid channels, while undervaluing organic search or even direct traffic.
It also leads to budget decisions based on faulty data. In either case, decisions made on data that consider attribution in a silo are faulty ones for most brands .Even with incrementality testing, that in theory controls for attribution bias, there can be issues.
Savings can be attributed to fixing attribution:
What we recommend:
Use a cross-platform testing platform that lets you build holdouts and unify taxonomy across campaigns.
Design holdouts that abide to allowed audience splits.
Leverage raw ad platform data mapped to a business, meaningful taxonomy, and business-sourced total conversions data to model incrementality.
When analyzing results, consider factors that might skew the measurement (e.g. self-optimizing platforms) and how that might change the decisions you make based on the results before you run the test, not after.
Run ongoing incrementality tests, not one-and-done experiments.
Map paid and organic together when evaluating top-of-funnel performance.
Incrementality doesn’t have to be a guessing game, but you need the right framework in place to get real answers.
GA4 Data Reliability & Integration
Since the switch to GA4, we’ve seen a surge in tracking headaches. It’s not that GA4 is broken, it’s that many teams rely on it to reconcile platform data and drive reporting dashboards. But GA4 doesn’t always sync cleanly with everything else.
Here’s what we’ve seen go wrong:
GA4 data lags behind real-time performance, which delays optimization
Revenue in GA4 doesn’t match backend systems, causing reporting conflicts
A/B test data often doesn’t align with GA4 sessions or events
Key events are misconfigured or underreported due to GA4’s stricter event model
How we help clients fix this:
Integrate GA4 with other platforms via a Customer Data Platform (CDP) to unify user-level data
Create source-of-truth dashboards that include backend data, not just GA4
Align testing platforms with GA4 event structure to ensure clean comparisons
GA4 can be a powerful part of your analytics stack, but only if it’s connected to everything else.
Consent Management & Privacy Compliance
Marketing teams need to prioritize tracking and consent management because tracking issues can occasionally turn into legal issues. Privacy regulations like GDPR and CPRA are becoming stricter, and many businesses aren’t ready. We’ve seen major data loss and even risk exposure due to simple missteps in consent setup.
Here’s what typically goes wrong:
Consent Management Platforms (CMPs) fire too late or not at all
Tags run before consent is granted, leading to compliance risks
Cookie categories aren’t mapped correctly in GTM, causing incorrect cookies to fire
Cookie deprecation isn’t planned for, so key audiences can disappear because steps haven’t been taken to solve for lost cookie data
These gaps could mean lost data and legal trouble.
How we help:
We run audits using tools like ObservePoint to check tag behavior against consent status
We configure CMPs (like OneTrust) to block tags until users opt in, mapped by cookie category
We support clients with server-side tracking and cookieless solutions to maintain data flow
You can’t afford to guess when it comes to consent. A single misfire can cost you visibility and trust.
Cross-Platform & Funnel Visibility
Even with great tracking on individual platforms, we still see clients struggle with stitching it all together. In our experience, teams often struggle to connect the dots between a user’s first ad exposure and their final conversion, especially across devices, platforms, and channels.
Common problems include:
No consistent customer ID across tools
Offline or backend actions (like CRM updates or sales calls) not tied to digital campaigns
Metrics that mean different things across platforms (e.g., “conversions” in Facebook vs. Google Ads)
The result is fragmented customer journey tracking and incomplete funnel visibility.
Here’s how we address it:
Implement first-party data strategies that collect and unify customer IDs
Use platforms like Segment or Tealium to connect CRM and analytics data
Build funnel dashboards that reflect the full customer path, not just last-click attribution
Without complete visibility, optimization becomes a matter of guesswork. Clean data across platforms turns your funnel from a black box into a roadmap.
Custom Tracking & Tagging Infrastructure
Every client wants data tailored to their business, but too often, custom tracking setups become unmanageable over time. We’ve seen teams inherit messy GA4 configurations, inconsistent UTM naming conventions, and dashboards that pull data from five sources with little to no alignment.
That makes auditing a nightmare and decision-making unreliable.
Common breakdowns we’ve seen:
Event tracking is implemented manually, inconsistently, or without clear documentation
Tools like Claravine or Funnel.io are underused or misconfigured
Data (SEO, paid media, etc.) and backend teams all report on different numbers
How we fix it:
Run full tag audits to spot inconsistencies or redundancies
Standardize UTM frameworks and naming conventions across channels
Set up integrated dashboards that map channel and revenue data in one view
Clients need a more complex measurement solution to accommodate today’s users. The modern customer is more mature and selective. They’re doing more research on who you are as a brand, across channels, before they convert. Teams are doing a great job of implementing multiple channels to bring these customers into the fold, but you need to implement a unified solution to make the most of the data they provide.
Tracking Issues in 2025 vs 2024
Tracking in 2025 looks very different from where we were just a year ago.
Last year, the biggest issues were setup-related: getting GA4 live, consistently tagging campaigns, and stitching data together across ad platforms. Clients were exploring tools and figuring out where things were breaking.
This year, the challenges have matured. Now it’s about optimizing what’s in place, shifting from basic implementation to smarter, scalable solutions.
What’s changed:
Tagging stability has improved, but the pressure is on to prove ROI with less data
Consent compliance and cookie deprecation are non-negotiable, not “nice to haves”
Incrementality testing and attribution refinement are top priorities
Teams are pushing beyond dashboards to revenue-backed insights
New platforms (like ArtsAI and OptiMine) are being evaluated with deeper scrutiny
The takeaway: In 2024, it was about getting things up and running. In 2025, it’s about whether your setup can scale, adapt, and stay compliant.
How You Can Start Improving Your Data Tracking Today
If you’re running into tracking issues or even suspect something’s off, don’t wait for a reporting crisis to assess the situation. You’ll save yourself time and headaches by looking into the issue now.
Here’s where we recommend starting:
Run a Full Audit: Use tools like ObservePoint to validate which tags are firing, where, and under what conditions. Focus on consent compliance, event coverage, and load order.
Standardize UTM and Taxonomy: Create a documented framework across your paid, organic, and internal teams. Inconsistent naming kills cross-platform clarity.
Reconcile GA4 With Backend Data: Build a dashboard that includes both GA4 and revenue data from your CRM or database. That’s your source of truth. Don’t only rely on platform-reported numbers.
Fix Consent Setup: Audit your consent management platform (CMP) setup and make sure no tags fire before consent. Use active group triggers (like in OneTrust) mapped to tag categories.
Rethink Attribution: Move beyond last click. Explore incrementality testing or multi-touch attribution models that actually reflect how your audience buys.
If your tracking setup isn’t solid, your data and every decision built on it is at risk. From attribution errors to consent gaps, we’ve seen how small misfires create major problems. But the good news is that most of these issues are fixable with the right audits and tools in place.
Whether you’re optimizing GA4, cleaning up cross-platform reporting, or getting your consent setup compliant, now’s the time to level up. Better data means better marketing, and it starts with tracking that works.
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Google is rolling out a new Data Manager API that lets you plug first-party data into Google’s AI-powered ad tools with less friction. The goal: stronger measurement, smarter targeting, and better performance without the hassle of managing multiple systems.
Why we care. The Data Manager API helps you get more value from the data you already have by sending reliable first-party data into Google’s AI. This improves your targeting, measurement, and bidding. It also replaces several separate APIs with one easy connection, cutting down on engineering work and getting insights back into your campaigns faster.
About the Data Manager API. It will replace several separate Google platform APIs with one centralized integration point for advertisers, agencies, and developers. It builds on Google’s existing codeless Data Manager tool, which tens of thousands of advertisers already use to activate their first-party data.
You can use it to:
Upload and refresh audience lists.
Send offline conversions to improve measurement.
Improve bidding performance by giving Google AI richer signals.
Partnership push. To speed adoption, Google is launching with integrations from AdSwerve, Customerlabs, Data Hash, Fifty Five, Hightouch, Jellyfish, Lytics, Tealium, Treasure Data, Zapier, and others.
Available today. The API is available starting today across Google Ads, Google Analytics and Display & Video 360, with more product integrations on the way.
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Generative systems like ChatGPT, Gemini, Claude, and Perplexity are quietly taking over the early parts of discovery – the “what should I know?” stage that once sent millions of people to your website.
Visibility now isn’t just about who ranks. It’s about who gets referenced inside the models that guide those decisions.
The metrics we’ve lived by – impressions, sessions, CTR – still matter, but they no longer tell the full story.
Mentions, citations, and structured visibility signals are becoming the new levers of trust and the path to revenue.
This article pulls together data from Siege Media’s two-year content performance study, Grow and Convert’s conversion findings, Seer Interactive’s AI Overview research, and what we’re seeing firsthand inside generative platforms.
Together, they offer a clearer view of where visibility, engagement, and buying intent are actually moving as AI takes over more of the user journey – and has its eye on even more.
Content type popularity and engagement trends
In a robust study, the folks at Siege Media analyzed two years of performance across various industry blogs, covering more than 7.2 million sessions. It’s an impressive dataset, and kudos to them for sharing it publicly.
A disclaimer worth noting: the data focuses on blog content, so these trends may not map directly to other formats such as videos, documentation, or landing pages.
With that in mind, here’s a run-through of what they surfaced.
TL;DR of the Siege Media study
Pricing and cost content saw the strongest growth over the past two years, while top-of-funnel guides and “how-to” posts declined sharply.
They suggest that pricing pages gained ground at the expense of TOFU content. I interpret this differently.
Pricing content didn’t simply replace TOFU because the relationship isn’t zero-sum.
As user patterns evolve, buyers increasingly start with generative research, then move to high-intent queries like pricing or comparisons as they get closer to a decision.
That distinction – correlation vs. causation – matters a lot in understanding what’s really changing.
The data shows major growth in pricing pages, calculators, and comparison content.
Meanwhile, guides and tutorials – the backbone of legacy SEO – took a sharp hit.
Keep that drop in mind. We’ll circle back to it later.
Interestingly, every major content category saw an increase in engagement. That makes sense.
As users complete more of their research inside generative engines, they reach your site later in the journey or for additional details, when they’re already motivated and ready to act.
If you’re a data-driven SEO, this might sound like a green light to focus exclusively on bottom-of-funnel content.
Why bother with top-of-funnel “traffic” that doesn’t convert?
Leave that for the suckers chasing GEO visibility metrics for vanity, right?
But of course, this is SEO, so I have to say it …
Did you expect me to say, “It depends?”
Here’s a question instead: when that high-intent user typed the query that surfaced a case study, pricing page, or comparison page, where did they first learn the brand existed?
I can’t believe I’m saying this, but you’ll have to keep making TOFU content.
You might need to make even more of it.
Let’s think about legacy SEO.
If we look back – waaaaay back – to 2023 and a study from Grow and Convert, we see that while there is far more TOFU traffic…
…it converts far worse.
Note: They only looked at one client, so take it with a grain of salt. However, the direction still aligns with other studies and our instincts.
This pattern also shows up across channels like PPC, which is why TOFU keywords are generally cheaper than BOFU.
The conversion rate is higher at the bottom of the funnel.
Now we’re seeing this shift carry over to generative engines, except that generative engines cover the TOFU journey almost entirely.
Rather than clicking through a series of low-conversion content pieces as they move through the funnel, users stay inside the generative experience through TOFU and often MOFU, then click through or shift to another channel (search or direct) only when it’s time to convert.
For example, when I asked ChatGPT to help me plan a trip to the Outer Banks:
After a dozen back-and-forths planning a trip and deciding what to eat, I wanted to find out where to stay.
That journey took me through many steps and gave me multiple chances to encounter different brands and filtering or refinement options.
I eventually landed on my BOFU prompt, “Some specific companies would be great.”
From there, I might click the links or search for the company names on Google.
What matters about this journey – apart from the fact that my final query would be practically useless as insight in something like Search Console – is that throughout the TOFU and MOFU stages, I was seeing citations and encountering brands I would rely on later.
Once I switched into conversion mode, I wanted help making decisions. That’s where I’m likely to click through to a few companies to find a rental.
So, when we read statistics like Pew’s finding that AI Overviews reduce CTR by upwards of 50%, and then consider what happens when AI Mode hits the browser, it’s easy to worry about where your traffic goes. Add to that ChatGPT’s 700 million weekly active users (and growing):
And according to their research on how users engage with it:
We can see a clear TOFU hit and very little BOFU usage.
So, on top of the ~50% hit you may be taking from AI Overviews, 700+ million people are going to ChatGPT and other generative platforms for their top-of-funnel needs.
I did exactly that above with my trip planning to the OBX.
The good news is that while that vacation rental company or blue widget manufacturer might not see me on their site when I’m figuring out what to do – or what a blue widget even is – I’m still going to take the same number of holidays and buy the same number of products I would have without AI Overviews or ChatGPT, Claude, Perplexity, etc.
Unless you’re a publisher or make money off impressions, you’ll still have the same amount of money to be made.
It just might take fewer website visits to do it.
More about TOFU
Traffic at the bottom of the funnel is holding steady for now (more on that below), but the top of the funnel is being replaced quickly by generative conversations rather than visits.
The question is whether being included in those conversations affects your CTR further down the funnel.
The folks at Seer Interactive found that organic clicks rose from 0.6% to 1.08% when a site was cited in AI Overviews.
And while the traffic was far lower, ChatGPT had a conversion rate of 16% compared with Google organic’s 1.8%.
If we look at the conversion rate for organic traffic at the bottom of the funnel – which we saw above – it was 4.78%.
Users who engage with generative engines clearly get further into their decision-making than users who reach BOFU queries through organic search.
But why?
While I can’t be certain, I agree with Seer’s conclusion that AI-driven users are pre-sold during the TOFU stage.
They’ve already encountered your brand and trust the system to interpret their needs. When it’s time to convert, they’re almost ready with their credit card.
Why bottom-funnel stability won’t last much longer
Above, I noted that “traffic at the bottom of the funnel is holding steady for now.”
It’s only fair to warn you that through 2026 and 2027, we’ll likely see this erode.
The same number of people will still travel and still buy blue widgets.
They just won’t book or buy them themselves. And at best, attribution will be even worse than it is today.
I spoke at SMX Advanced last spring about the rise of AI agents.
I won’t get into all the gory details here, but the Cliff Notes are this:
Agents are AI systems with some autonomy that complete tasks humans otherwise would.
They’re rising quickly – it’s the dominant topic for those of us working in AI – and that growth isn’t slowing anytime soon. You need to be ready.
A few concepts to familiarize yourself with, if you want to understand what’s coming, are:
AP2 (Agent Payments Protocol): A standard that allows agents to securely execute payments on your behalf. Think of it as a digital letter of credit that ensures the agent can only buy the specific “blue widget” you approved within the price limit you set. Before you say, “But I’d never send a machine to do a human’s job,” let me tell you, you will. And if you somehow prove me wrong individually out of spite, your customers will.
Gemini Computer Use Model API: A model with reasoning and image understanding that can navigate and engage with user interfaces like websites. While many agentic systems access data via APIs, this model (OpenAI has one too, as do others) lets the agent interact with visual interfaces to access information it normally couldn’t – navigating filters, logins, and more if given the power.
MCP (Model Context Protocol): An emerging standard acting as a universal USB port for AI apps. It lets agents safely connect to your internal data (like checking your calendar or reading your emails) to make purchasing decisions with full context and to work interactively with other agents. Hat tip to Ahrefs for building an awesome MCP server.
Why do these protocols matter to a content strategist?
Because once AP2 and Computer Use hit critical mass, the click – that sacred metric we’ve optimized for two decades – changes function.
It stops being a navigation step for a human exploring a website and becomes a transactional step for a machine executing a task.
If an agent uses Computer Use to navigate your pricing page and AP2 to pay for the subscription, the human user never sees your bottom-of-the-funnel content.
So in that world, who – or rather, what – are you optimizing for?
This brings us back to the Siege Media data.
Right now, pricing pages and calculators are winning because humans are using AI to research (TOFU and MOFU) and then manually visiting sites to convert (BOFU).
But as agents take over execution, that manual visit disappears. The “traffic” to your pricing page may be bots verifying costs, not humans persuaded by your copy.
The 2026 strategy
This reality pushes value back up the funnel.
If the agent handles the purchase, the human decision – the “moment of truth” – happens entirely inside the chat interface or agentic system during the research phase.
In this world, you don’t win by having the flashiest pricing page.
You win by being the brand the LLM recommends when the user asks, “Who should I trust?”
Your strategy for 2026 requires a two-pronged approach:
For the agent (the execution): Ensure your BOFU content is technically flawless. Use clean schema, accessible APIs, and clear data structures so that when an agent arrives via MCP or Computer Use to execute a transaction, it encounters no friction.
For the human (the selection): Double down on TOFU. Focus on mentions and citations. You need to be the entity referenced in the generative answer so that users – and agents – trust you.
As we move toward 2026 and then 2027 (it’ll be here sooner than you think), the “click” will become a commodity more often handled by machines.
The mention, however, remains the domain of human trust. And in my opinion, that’s where your next battle for visibility will be fought.
Time to start – or hopefully keep – making the TOFU.
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