The Average Buyer Now Needs 6 Touchpoints Before They Convert

That number used to be 2.

Fifteen years ago, most purchase decisions involved just a couple of interactions with a brand before someone bought. A 2025 study now puts the average at 6 touchpoints, with 73% of shoppers regularly moving across multiple channels before they buy. McKinsey's 2024 B2B Pulse Survey found that B2B buyers now use an average of 10 interaction channels across their buying journey, up from just 5 in 2016. That's the number of channels doubling in under a decade and that's before you account for AI research tools which didn't meaningfully exist as a buying behaviour in 2016. And the pace isn't slowing: HockeyStack's analysis of 150 B2B SaaS companies measured a 19.8% year-on-year increase in touchpoints to close a deal from 2023 to 2024.

And those are just the touchpoints we can see.

This matters because a lot of paid media strategy is still built around capturing someone at the point they're ready to buy. That made more sense when the journey was short. It makes less sense now and it's actively costing some accounts.

The Journey Looks Very Different Depending on What You Sell

Before going any further, it's worth being honest about something: the 6 touchpoint average is exactly that, an average. It masks an enormous amount of variation between industries and purchase types.

Someone buying a pair of trainers might search, click an ad, browse and buy within the same session. Someone buying a sofa might spend three weeks visiting brand websites, reading reviews, watching YouTube comparisons, visiting a showroom and then converting through a retargeting ad. Someone choosing an accountant, a piece of enterprise software, or a legal service might take six months, visit your site a dozen times, read every case study you've published, look you up on LinkedIn, ask peers for recommendations and still not be ready to pick up the phone.

That variation matters a lot for how you measure and fund campaigns.

For eCommerce, the challenge is that even relatively short journeys now involve more channels and more touchpoints than they used to. Consumers move fluidly between social discovery, search, review sites and email before converting. The window might be days rather than months, but there's still a meaningful journey happening and even data-driven attribution will only show you the trackable part of it. The touchpoints that happened on TikTok, in a WhatsApp recommendation, or through an AI tool won't appear anywhere in your reporting.

For B2B and lead gen, the stakes are higher because the journeys are longer and the buying decisions are more considered. Forrester's 2026 State of Business Buying report found the typical B2B buying decision now involves 13 internal stakeholders and 9 external influencers. That's not a funnel, it's a committee. And Gartner's March 2026 survey found that 67% of B2B buyers now prefer a rep-free experience, with 45% using AI tools during a recent purchase. Buyers are doing more of their decision-making independently, across more channels, before they ever engage with anyone.

The reason this matters for campaign management is straightforward. If your measurement strategy is built around one conversion event at the end of that journey, you are blind to everything that happens before it. You have no way of knowing which campaigns are building the intent that eventually converts, which channels are reaching people early in the process, or which activity is doing nothing at all.

That gap between what you can see and what's actually happening is where budget decisions go wrong.

The Visibility Problem Is Getting Worse

It's not just that there are more touchpoints. It's that a significant chunk of them now happen somewhere you can't track at all.

AI tools like ChatGPT, Perplexity and Google's AI Overviews have become a genuine research layer for consumers before they ever enter your funnel. By February 2026, ChatGPT had reached 900 million weekly active users according to OpenAI. Adobe's May 2025 research found that 36% of users discovered a new product or brand through ChatGPT, rising to 47% among Gen Z. And Gartner's March 2026 data confirms that nearly half of B2B buyers are already using AI tools as part of the purchasing process itself.

None of that shows up in your attribution data.

For eCommerce, this plays out as product and brand discovery happening on AI platforms before a user ever reaches Google or your website. Someone asking ChatGPT "what's the best sustainable running shoe under £100" might get a direct recommendation and then search that brand name. Your account records a branded search conversion. The AI research that drove it is invisible.

For B2B and lead gen, it runs even deeper. Buyers are using AI tools to research categories, compare vendors, evaluate solutions and shape their requirements before they engage anyone. They arrive at your site already informed and already opinionated, having completed significant parts of the buying process in places you have no visibility of.

And it's not just AI. Seer Interactive's analysis of over 3,100 queries across 42 organisations found paid CTRs on queries where AI Overviews appear dropped by 68% between June 2024 and September 2025 and their projections recommend planning for CTRs on high-funnel queries to be 20 to 30% lower throughout 2026. Their April 2026 update shows some early signs of stabilisation, but CTRs remain well below pre-AIO levels. Users who do click after AI-assisted research tend to show stronger intent. But there are fewer of them and the journey that shaped their decision is invisible.

The journey is getting longer. The visible portion of it is getting shorter. That's the problem.

What This Does to Your Campaigns

This plays out in three specific ways regardless of whether you're running eCommerce, B2B, or lead gen.

Upper-funnel activity looks weaker than it is. Display, paid social awareness, video: these channels build familiarity and seed intent. But if the research journey they start continues on AI platforms or through organic discovery before returning to paid search, the link between that spend and the eventual conversion is broken in your data. Campaigns get paused. Budgets get pulled. Demand quietly dries up a few months later and nobody immediately connects the two things. For eCommerce this might mean cutting a prospecting campaign that was genuinely introducing your brand to new buyers. For B2B it often means gutting awareness activity and wondering six months later why pipeline has dried up.

Branded search looks like it's doing more than it is. When someone completes a long research journey and searches your brand name directly, branded campaigns perform brilliantly. Low CPCs, high conversion rates. It's easy to credit that as the channel doing the heavy lifting, when really it's the final step of a journey you didn't fund. This is true in eCommerce where a customer might have seen three Instagram posts, read two reviews and watched a YouTube video before ever typing your brand name into Google. It's true in B2B where a prospect may have consumed six pieces of your content anonymously before that branded search ever appeared.

Automated campaign types are working from an incomplete picture. Performance Max, smart bidding, broad match: all of these learn from your conversion signals. If those signals are increasingly skewed toward last-visible touchpoints, you're feeding your automation a distorted picture of what's actually working. In eCommerce that means smart shopping campaigns optimising toward people who look like they're already close to buying, missing the broader audience that needs warming up first. In B2B it means Performance Max finding people who look like the small set of users who filled in a demo form, rather than the much larger pool of people who are in the research phase but not yet ready to convert.

A Click Is a Weak Signal. You Need Stronger Ones.

This is where a lot of campaigns fall down, particularly in categories where the buying journey is long.

Getting someone to click your ad and land on your site isn't a meaningful signal of intent on its own. It tells you they were curious enough to click. It doesn't tell you whether they're a genuine prospect, how close they are to a decision, or whether your site gave them what they needed to move forward.

For campaigns to work properly in 2026, you need to be tracking signals that actually indicate progression through the journey. That's where the distinction between macro and micro conversions becomes important.

A macro conversion is the primary action you ultimately want someone to take. For eCommerce that's a purchase. For B2B or lead gen it's a form submission, a demo request, a phone call. It's the moment someone crosses the line from prospect to lead or customer.

A micro conversion is a smaller on-site behaviour that indicates someone is genuinely progressing toward that point. Not just browsing, but engaging in a way that suggests real intent. The key word there is genuine, not every on-site interaction is a positive signal and adding micro conversions without thinking critically about what each behaviour actually means can make your data worse, not better.

In B2B and lead gen, this distinction is critical. Not everyone who is a genuine prospect is ready to share their details yet. Given that 67% of B2B buyers now prefer to complete as much of the process as possible without engaging anyone, your website is doing far more of the selling work than it used to. The engagement signals on that site are telling you who's serious,  but only if you're tracking the right ones.

Useful B2B micro conversions to consider tracking include things like:

• Watching an embedded video all the way through, not just playing it

• Reading a case study to the end rather than bouncing halfway through

• Visiting the pricing page and clicking a "contact for pricing" button

• Starting a form but not completing it

• Using a chatbot

• Clicking a phone number, email address, or physical address in a contact section

• Visiting an about us page and clicking through to team LinkedIn profiles, particularly sales or leadership profiles

That last one is worth pausing on. Someone who visits your about us page and clicks through to your sales director's LinkedIn profile is doing research. They're checking who they'd be dealing with. That's a strong behavioural signal that deserves to be weighted in your campaign data.

In eCommerce, the same principle applies but the signals look different. Strong micro conversions are behaviours that indicate genuine purchase intent: adding a product to the basket, saving an item to a wishlist, signing up to the newsletter, or returning to the same product page multiple times. These all suggest someone moving toward a decision.

But this is where you need to be careful. Not every interaction means what it looks like. Someone using a size guide and then leaving immediately might not be a positive signal at all,  they may have checked the sizing, realised it didn't work for them and dropped off. If you track that as a positive micro conversion and feed it to your bidding, you're asking the algorithm to find more people who are likely to leave. The question to ask about any micro conversion is: what does the data tell me happens next for people who complete this action? If they tend to convert, it's a positive signal worth tracking. If they tend to drop off, it's a friction point worth fixing, not a conversion event worth bidding on.

These micro conversion signals can be fed directly back into your campaigns. Smart bidding can be trained on engagement signals as well as final conversions. Audiences can be built around people who completed specific on-site actions. When you have richer, more accurate signals going in, the automated systems have a much clearer picture of what a valuable user actually looks like.

If you're running Performance Max for eCommerce and your only conversion event is a completed purchase, you're asking the algorithm to find people who look like your existing buyers and nothing else. Feed it basket adds, wishlist saves and meaningful product page engagement and the picture gets significantly richer. If you're running Performance Max for lead gen and your only conversion event is a form submission, you're asking the algorithm to find people who look like a very small, very bottom-of-funnel set of users. Feed it stronger mid-funnel signals and the whole campaign learns differently.

What to Actually Do About It

Start by understanding what your journey actually looks like. Not what you think it looks like, what the data tells you. How many channels are your converting customers touching before they buy? How long does that process take in your category? For eCommerce this might be days. For B2B or considered lead gen it could be months. The answer should shape everything else in this list. If you haven't mapped this, that's the first job.

Map your conversion events to match the journey, not just the end goal. Audit what you're currently tracking and ask honestly whether it reflects how your customers actually move toward a decision. If you only have one macro conversion and nothing else, that's where to start. For eCommerce that means adding basket adds, newsletter sign-ups and product engagement. For B2B and lead gen it means identifying the on-site engagement signals that indicate a serious prospect and building those into your tracking before they ever fill in a form.

Assign values to your micro conversions. You don't need to be precise, but giving relative weight to different engagement signals helps smart bidding understand what matters. In B2B, a case study read-through isn't worth the same as a demo request, but it's worth more than a pageview. In eCommerce, a basket add isn't worth the same as a purchase, but it signals far stronger intent than a product view. Give the algorithm something to work with beyond the final step.

Don't make budget decisions based on last-touch data alone. Look at assisted conversions, branded search volume trends and direct traffic patterns alongside your primary conversion data. If you cut an awareness channel and branded search volume drops six weeks later, that's your signal. This applies in eCommerce just as much as B2B. A Meta awareness campaign that shows no direct conversions in reporting might still be responsible for the intent that shows up in search two weeks later. And remember, even with data-driven attribution doing its job, none of this accounts for the AI-driven research that happens before someone enters your trackable funnel at all. If you're still on last-click attribution, changing to data-driven is the immediate first step before any of this analysis is worth doing.

Protect activity that supports the journey, not just activity that closes it. With McKinsey confirming that buyers now move across an average of 10 channels before converting, a strategy built around 2 or 3 channels is structurally incomplete. Awareness campaigns, consideration content, retargeting sequences: these move people through a process that is longer and less linear than it used to be. If you're only funding the bottom, you're harvesting demand you're not creating. In eCommerce that might mean protecting prospecting campaigns even when they don't show direct ROAS. In B2B it means not cutting content-led activity just because it doesn't show a direct conversion in your reporting.

Review your negative keyword strategy. Blocking terms like "how", "what" or "best" can cut you off from users who are early in a research journey across both eCommerce and B2B. In eCommerce those searches often signal someone in the consideration phase who is close to a purchase decision. In B2B they represent someone mapping out their options. Those aren't low-value searches. They're people at the start of a path that might end with your brand.

Think about where your brand exists before the click. With 36% of users now discovering brands through ChatGPT and 45% of B2B buyers using AI tools during a recent purchase, your presence in AI environments is part of your acquisition strategy now whether you've planned for it or not. For eCommerce this means thinking about whether your products and brand are appearing in AI-generated recommendations. For B2B it means asking whether your content is the kind that gets cited, whether you're appearing when someone asks an AI tool for the best solution in your category and whether your website is doing enough of the selling work for buyers who will never pick up the phone until they're already convinced.

🔹 Final Thoughts

The one-click buyer was always a simplification. In 2026, the gap between that simplification and how people actually buy has never been wider.

Whether you're running eCommerce, B2B, or lead gen, the fundamentals are the same: journeys are longer, more fragmented and a growing portion of them now happen in places that generate no trackable data at all. The signals we do have access to are getting noisier, not cleaner and automated systems are only as good as what we feed them.

That doesn't mean paid media is broken. It means the way we measure it, fund it and interpret it needs to catch up with how people actually make decisions. Not just the final step. The whole journey.

Understanding that journey, building your measurement around it and protecting the activity that supports it is what separates accounts that perform from accounts that slowly erode.