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Made With Intent and Dynamic Yield comparison

If you've been racking your brain about whether to pick Made With Intent or Dynamic Yield, you can stop right here. Our detailed breakdown is here in all its glory.

Made With Intent is an on-site intent engine for eCommerce businesses. It reads buying intent in real time and decides which experiences go to which visitors, and when.

Dynamic Yield is an experience optimization and personalization platform. It helps businesses tailor digital customer journeys across websites, mobile apps, and email.

This post explains where the two platforms work together, and where you'd still use Dynamic Yield instead.

If you can't wait until the end, here's a TLDR;

Pick Dynamic Yield if:

• Your priority is consistent personalisation across web, mobile app, email, and in-store kiosk

• You've got the team and budget to do a weeks long enterprise deployment

• Recommendation capabilities matters more than first-page view intent coverage.

Made With Intent is for you if:

• You want to read buying intent in real-time

◦ Then, serve the right content, the right experience at the appropriate moment

• Want to benefit from a 30-60 minute install time

And when we're thinking about Made With Intent and Dynamic Yield working together, here's how we recommend thinking about it:

Made With Intent decides what experiences you should serve, to who and when, and Dynamic Yield delivers those experiences.

How Made With Intent is different to Dynamic Yield

There's three things that Made With Intent does different to Dynamic Yield. Let's dig into them below:

1. Made With Intent reads intent in real time

Dynamic Yield's intent workflow utilises two routes. First, Empathic Personalization classifies visitors into four inferred states, which are Curious, Interested, Focused and Satisfied.

Its Audience Hub lets teams hand-build "low / medium / high intent" audiences from rules. Dynamic Yield's Primary Audiences framework shows a leading golf retailer defining low intent as fewer than 12 page views per session and high intent as more than 24.

That's a useful starting estimate, but page views aren't intent. A hesitant shopper racks up more pages than a decisive one. A high-intent visitor often converts inside three.

The more common version isn't pageview counts — it's event proxies. Add to cart equals high intent. Wishlist equals consideration. But an add to cart is as often a price check, a size comparison or a shipping-cost probe as it is a purchase signal. The event tells you what happened. It doesn't tell you what it meant.

Now, this is pretty fundamental: Dynamic Yield's model relies on behaviours your shoppers have already exhibited. It's a snapshot backwards in time, and like many what we call "rules-based" personalisation tools, you're reacting to things that have already have happened. Unlike Made With Intent.

Made With Intent reads buying intent directly — multi-dimensional, second-by-second signals predicting where the visitor is in their decision right now.

We break downs shopper behaviour into six stages, and these are: Intent stage. Intent signals. Intent trends. Purchase confidence. Abandon risk. Shopper mindset.

All updated every three–five seconds during a live session, on a model trained across 150+ retailers and 50 billion+ events.

2. Allocation across hundreds of intent combinations and not post-test segmentation

It takes eCommerce teams considerable time to build and maintain audience rules in Dynamic Yield. For instance, coding things such as "low intent equals fewer than 12 page views, high intent equals more than 24," then QA-ing those cohorts and redesigning them after each test.

Made With Intent replaces that with continuous intent prediction and delivery. The model decides who sees what, in real time, across hundreds of intent combinations. The actual grunt work is handled by our agent. Your team focuses on strategy, creative, and proof.

Our agent retrains daily, so the experience keeps allocating toward the intent combinations where impact is actually felt. Always on, always learning, always improving on where it started.

3. First-pageview coverage — no fallback needed

Behavioural data takes time to accrue; for anonymous or first-time visitors, Dynamic Yield falls back to geo-based predictive targeting and contextual signals.

Made With Intent has no fallback by design. It doesn't need one. We've trained it across 50bn+ events, in a range of contexts, giving the model day-one predictive power on every visitor, anonymous, identified, first-time, returning.

Made With Intent and Dynamic Yield: In depth

There are lots of areas of cross-over between Made With Intent and Dynamic Yield. The way our technologies work is similar in principle, but different in its practical implementation.

Let's start first with how Dynamic Yield's prediction capabilities work:

How Dynamic Yield's prediction works

Dimension	Dynamic Yield (AdaptML)	Made With Intent
Core model output	Recommendations, audience affinities, content variants	Multi-dimensional buying intent per visitor
What it predicts	Which item / content / offer is most relevant	Intent stage, signals, trends, purchase confidence, abandon risk, shopper mindset
Underlying architecture	NextML (NLP) + AffinityML (LSTM RNN)	Multi-input, multi-output deep learning framework with ~800 behavioural signals and ~600 real-time per-visitor/session features
Signal type	Historical patterns + live session data	Live behavioural micro-signals (scroll hesitation, comparison patterns, dwell time, momentum shifts)
Update frequency	Continuously self-trains; predictions exposed at decision points (page loads, content surfaces)	Predictions update every 3–5 seconds during a live session; model retrains nightly
Training data	Per-merchant historical patterns	50bn+ events across 150+ retailers
Validation	DY-published — confident but not externally benchmarked	AUC ~0.83–0.84 on conversion/exit/return/add-to-cart heads, calibrated probabilities

While we're talking about AdaptML, we have to say, it's a really sophisticated bit of engineering. It utilises recurrent neural networks and NLP models to get smarter and smarter as it consume more data its got on a specific retailer's visitors.

However, it predicts what you'd expect (affinity and relevance), not what's happening in a visitor's decision right now.

Our model is a driven by a single purpose: it reads buying intent. Sure, it's a narrower job, but it's the one that determines whether a visitor converts, hesitates, or leaves.

Made With Intent vs Dynamic Yield

Capability	Dynamic Yield	Made With Intent
Core job	Cross-channel personalisation engine (content, recs, audiences, testing)	On-site intent engine (intent read + agentic allocation + causal measurement)
Works on	All identified visitors fully; anonymous via geo/contextual fallback	Every visitor from the first pageview, no fallback needed
What it predicts	Content/product affinity, audience membership	Multi-dimensional intent: stage, signals, trends, confidence, abandon risk, mindset
Signal type	Historical + live session data, organised by audience rules	~800 live behavioural signals per event; continuous micro-signal read
On-site experiences	WYSIWYG with mature templates and custom code; targeted by audience/rule	WYSIWYG + agentic campaigns; targeted by live intent
Allocation method	Static — predefined audience and variant, results read post-hoc	Dynamic — agent allocates across hundreds of intent combinations during the campaign
Measurement	Bayesian A/B between variants; holdback optional and manually configured	Bayesian A/B with holdback on every experience by default; reports causal incremental revenue
Multi-channel reach	Web, mobile app, email, in-store kiosk	Web only; other channels via integration to ESP/ad stack
Platform support	Platform-agnostic via SDK/JS/server APIs	Platform-agnostic via single 7kb GTM tag
PII handling	Captures behavioural and identifiable data per setup	No PII; ISO 27001 certified
Time to live	Weeks to months (G2 reviews)	30–60 minutes via GTM
Ongoing maintenance	Configuration-heavy: Audience Hub rules, Empathic Personalization, Sections/Page Contexts/Selectors	Light: agentic campaigns reduce manual segmentation work after setup
Agentic campaigns	No agentic layer	Yes — strategy + tactics in, agent allocates dynamically

When you should pick Dynamic Yield

Hey, we're not here to blindly sell you Made With Intent. Sometimes, our tool just isn't right for your business. So, unlike loads of other SaaS vendors, let us tell you when we wouldn't be a good fit:

• If you're trying to do cross-channel, Dynamic Yield is the right choice versus Made With Intent. We're web-first, and for multi-channel personalisation programmes Dynamic Yield is the right option.

• Recommendations: NextML and AffinityML are purpose built models for product and content recommendations. Made With Intent adds an intent decison later but it is not a replacement for NextML or AffinityML.

• Sophisticated email personalisation: Klaviyo-grade dynamic content across email and ad placements out of the box. If email is a key part of what you do, Dynamic Yield is a top choice.

• Security of a big vendor: Dynamic Yield is an eight-time Gartner Magic Quadrant Leader for personalisation engines. If you're enterprise org and need to run a formal RFP, this helps your procurement team make a decision.

• Strong experience builder. Sections, Page Contexts, and Selectors give users very fine control. But only after you've climbed the initial learning curve.

Where Made With Intent wins

Of course, this is an article designed to help you pick between Dynamic Yield and Made With Intent. From our table above, it's clear there's plenty of areas of overlap, but there's some stuff we do that, we don't mind saying, makes us a better choice. Have a read:

• Acts on the anonymous majority: Every visitor gets a multi-dimensional intent read from the first pageview. No prior data, no behavioural accrual, no geo fallback.

• Multi-dimensional intent prediction: The way we predict intent is comprehensive. We use six measures: stage, signals, trends, purchase confidence, abandon risk and shopper mindset. These are all updated every three-five seconds, unlike Dynamic Yield.

• Autonomously runs campaigns and makes decisions under directives: Agentic Campaigns can dynamically allocate experiences across hundreds of intent combinations during a campaign you'll run. Dynamic Yields's models are sophisticated. The targeting layer above them is still rule-driven. That's simply how the tool is built. But it means what experiences are served is decided before the campaign runs, and not during it.

• Cross-merchant model: 50 billion+ events across 150+ retailers. Day-one predictive power for our customers.

• Start within 30 minutes: Single 7kb GTM tag, no PII and we're ISO 27001 accredited.

So, it's time to make a decision: Let's pick one. Or both?

It's crunch time. We've given you all the facts, but it's time to wrap up and make a judgment call.

Pick Dynamic Yield if the you want consistent cross-channel personalisation — content and recommendations spanning web, mobile app, email, and kiosk. And if you have the technical resources to operate it.

Dynamic Yield's breadth and recommendation algorithm depth is class-leading, and trying to replicate the scale of that capability with Made With intent, plus some integrations would be a worse outcome for you.

Choose Made With Intent if you want a on-site decisioning, intent-driven experiences, and proven incrementality. Our tool delivers experiences natively, allocates them dynamically across hundreds of intent combinations, and proves causal lift on every one.

Now, something to think about. If you're an enterprise customer, you actually could consider both. And here's why:

• Dynamic Yield gives you the breadth and means of channels and mediums to serve personalised content to

• Made With Intent helps you accurately decide who, and when that content should be served

That's brought us to the end of the comparison blog post. If you're still unsure of the differences between Dynamic Yield and Made With Intent, the best thing for you to do is talk with one of our team.

You can book a demo here.

Disclaimer: This comparison is based on publicly available information from Dynamic Yield's documentation, marketing site, and customer reviews as of April 2026. Both products evolve continuously. If anything looks out of date, get in touch and we'll sort it.

Jon Davis

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Read Time

August 10, 2026

Intent-led solutions

How to get started with intent-based email capture

Learn how to boost email sign-ups without annoying visitors by triggering capture at the right time, based on real-time intent, not fixed rules.

Charley Bader

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Read Time

Retailers ask for emails with the goal of growing their audience, their campaign reach, and their influence.

But most retailers are asking at the wrong time, in the wrong way, and it’s costing them.

In our Intent Gap research, we found 55% of online shoppers dislike pop-ups that appear early in a session. 45% say they actively make them less likely to buy. One in five even say they’d leave a site altogether if interrupted too soon.

37% of the retail sites analysed as part of the report used pop-ups, with 79% shown within the first 30 seconds.

The problem isn’t the capture itself. It’s the lack of context.

Most email capture strategies are built on fixed rules; time on site, page views, scroll depth. But these are proxies, not signals. They don’t reflect how a visitor is behaving or how likely they are to respond. They assume intent, rather than recognising it.

This isn’t about switching tactics. It’s about responding to behaviour in real time.

Rethink: Why you’re capturing emails

When email capture is treated as a numbers game, relevance drops. And the risk goes up. You might gain a contact in the short-term, but ultimately lose a customer.

The right question isn’t how do we collect more emails? It’s how do we make the exchange feel appropriate, valuable and well-timed. For both sides?

That means considering two things:

Mindset: Where is the customer in their journey? Are they focused and confident? Or showing signs of struggle, and unlikelihood to progress?
Value: What are you offering in return? Is it aligned to what they’re doing?

The best email capture doesn’t interrupt the journey. It supports it.

Optimise: Start capturing with Intent

To start with, optimise what already exists. Use intent segmentation to change when your capture prompts fire.

Play 1: Trigger email capture for abandoning visitors

Most email capture is delivered too soon, before visitors have shown any interest or given any signal that they’re ready for a value exchange.

The fix: Wait for signs of struggle or abandon, then trigger based on live behaviour.

Take On The Beach, who triggered capture only for visitors in the Engage or Build stages of the Intent Framework, who were showing subtle signs of drop-off. By adjusting the timing to match behaviour, they saw a 28% uplift in email sign-ups with no hit to conversion.

Why this works:

You reach the right audience, in-session
You increase sign-ups without sacrificing experience
You stop defaulting to time-based rules that overlook nuance

Play 2: Ask for an email when a visitor is unlikely to progress

Instead of waiting for signs of struggle, or abandon, you can also target a visitor when they’re indicating they’re unlikely to move forward in their journey, by using Intent to Progress.

That’s what Le Chameau did. By limiting email capture to visitors who were unlikely to progress, and excluding focused shoppers entirely, they:

Increased email sign-ups by 3%
Drove 24% incremental revenue
Protected high-value journeys from interruption

Grow: What comes next

Timing is essential. But message matters too.

Most capture prompts lead with a generic offer: “Sign up for 10% off.” But not everyone is looking to buy. And not everyone cares about a discount.

Visitors early on in their journey, who haven’t found the right product for them? Offer a newsletter prompt.

Shoppers who have a product affinity, but low likelihood to purchase? Suggest a save for later or price drop alert.

This approach moves email capture from a hard sell to a helpful nudge. Tailored to behaviour, aligned with intent.

It also opens the door to experimenting with softer incentives, different tones of voice, and varied placements. Especially for visitors who show high exit intent, but lower likelihood to return.

What happens when you get this right?

When email capture is powered by real-time intent:

Sign-up rates increase, because prompts are more timely and contextual
Conversion rates hold steady, because you don’t disrupt high-intent visitors
List quality improves, with fewer disengaged or disinterested contacts
Revenue grows, from visitors that may otherwise have been lost

Capture becomes strategic, not interruptive. And it builds long-term value in your customer base.

Your first three steps

If you’re looking to make an impact fast:

Replace time-based triggers with intent-led email capture prompts
Target abandoning or struggling visitors, and those unlikely to progress. Exclude focused shoppers
Align your offer or message to the visitor’s behaviour and mindset

From there, test new placements, value exchanges and copy aligned to intent predictions. And treat capture as a recurring opportunity, not a one-off chance.

Because when you understand visitor behaviour, you don’t have to interrupt to make an impact. You just have to respond at the right time.

Want to see how intent-first email capture works in practice? Get a demo to learn how Made With Intent helps teams grow their lists without damaging their visitors’ experience.

May 27, 2025

Intent-led solutions

Ecommerce's email capture issue: 9 leaders talks pop-ups & timing

Ecommerce brands are losing customers to generic email capture pop-ups. In this article, nine experts unpack the problem and share intent-driven ways to balance list building with CX.

Daniel Gripton

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Read Time

An engaged customer list is a valuable asset. It’s no wonder most retail websites go for the obvious way of growing it: triggering a pop-up to everyone. Often seconds after someone lands, or as they go to exit.

Yet, asking for someone's email address moments after they arrive feels abrupt and annoying. It’s not the best start to a new relationship, is it?

The thing is, eCommerce makes these things easy to overlook. For most teams, a visitor's reaction to the pop-up is only perceptible through proxy metrics like close or conversion rate. This doesn’t give you the full picture. What’s not measurable is the number of people who were there to buy but didn’t, because of the email capture.

So we asked shoppers.

Our Intent Gap report found that showing an email capture pop up too soon has a 1 in 5 chance of causing a visitor to abandon your site.

Let’s be clear. It’s not all email capture pop-ups that frustrate customers. Some are viewed as valuable and helpful, with conversion rates in high double figures. It all comes down to timing and context.

We’ve heard from the shoppers, so it’s only fair we did the same with the retailers. We spoke with nine ecommerce leaders to understand why a catch-all approach to email capture pop-ups is still the norm despite how they make shoppers feel.

The status quo of email capture

More than half of shoppers find pop-ups annoying. 1 in 5 dislike them so much it stops them from shopping. Yet, 79% of pop-ups are triggered within the first 30 seconds.

Is this the best approach we have in 2025 and beyond?

“How we shop online has changed a lot over the last 5-10 years, yet we’re still relying on the same tactics. Customers are more savvy, shopping across multiple websites and are protective over who they give their personal information to.”
Jackie Barnett, Head of CRM at MandM Direct

As Jackie points out, immediate email capture pop-ups might have worked 10 years ago, but today's shoppers are worried about data security. Plus, with overflowing inboxes, most people are reluctant to offer up their info. Time on site pop-ups might well be “the way we’ve always done it,” but it won’t wash with today’s customers.

Another reason the industry is stuck using an outdated method? FOMO.

“Most brands do email pop-ups early or on exit because it feels safe. Like, catch the visitor before they leave or bounce. It's a numbers game--more eyeballs, more chances.”
‍Natalia Lavrenenko, UGC manager/Marketing manager

It’s a numbers game when it should be a people game. Where’s the value in collecting 1000s of email addresses of annoyed people? Will they read your emails, or mark them as spam? That’s if the email’s even real.

So, what’s really at stake here?

“If you've got a lot of inbound organic traffic, combined with a good lead magnet, you can do well on that 1%-2% conversion on popups. The con is that you're annoying everybody else.”
‍Brenna Milleville, Founder at Elly and Grace

Capturing emails from a tiny percentage of all traffic while actively irritating the vast majority. It’s a pretty bad deal, and everyone knows it. So why is this method still being used?

“There's pressure to capture volume. Just like the pressure to send more marketing emails, even though we know it’s ineffective. It can be hard to justify more targeted efforts without data, especially when a belief persists that more activity = more revenue.”
‍Alfie Calas, Head of CRM at thortful

This is the reality for many ecommerce teams. Goals and targets that direct them away from doing better work.

It comes down to what can be measured and what data is available. While it’s obvious a smaller, engaged list will outperform a larger, disengaged one, having the data to prove it is the stumbling block.

“Customers who consent to email tend to have a higher LTV, so capturing their email is a priority. The more emails we have, the more customers we can keep speaking to, the more chance we’ve got at cost-effectively retaining them!”
Jackie Barnett, Head of CRM at MandM Direct

As Jackie shared, the rationale behind capturing every email address vs. just those that matter is the idea of chance.

Email capture pop-ups triggered after 30 seconds on-site equate to a scattergun approach based on a wish and a prayer. What’s ignored is the loss of potential immediate sales from the people put off.

This isn't news to ecommerce professionals, but it's not just the pressure of targets that has seen it become an accepted behaviour. It's the limitations of visitor data and the targeting options available in their tech stack.

“Most out-of-the-box tools only allow for a handful of triggers, so marketers are restricted in the ways they can be creative about approaching customers for email capture.”
‍Alfie Calas, Head of CRM at thortful

“The prevalent [email capture] methods don't consider the unique journey and mood of each visitor.”
‍Ben Read, CEO at Mercha

It’s worth reiterating; a web page tells you nothing about the customers’ buying stage.

So when tools are limited to triggering pop-ups based on page or time on site, you miss critical signals. Your experience becomes disconnected from the context of the visitor.

If retailers want to improve their relationship with customers, this status quo has to change. The focus needs to shift to the shopper and how they behave in the context of the whole experience. This is how we create higher opt-in percentages, less friction, and more meaningful lists.

The cost of generic email capture

So much effort goes into crafting the perfect welcome email series, the tone of voice, database segmentation, data security practices, etc. But so little goes into the moment when customers are asked to sign up. Yet there’s much at stake. 40% of shoppers say email capture pop ups make them less likely to buy.

“I've learned that how and when you ask for an email can make or break a relationship with customers…Focus on building relationships, not just lists.”
Asim Rahat, Founder at Oswin Hyde

Asim found out the hard way: get it wrong, and there’s rarely a second chance. A poorly-timed pop-up might get closed, but it also sets the tone.

So, what’s the real cost of generic, ill-timed pop-ups?

The negative shift in perception and lost sales you’ll never track.

“A huge issue is the unseen impact on people who find these pop-ups a total turn-off. What percentage of potential customers are being lost each day due to this one-size-fits-all approach? Plus, the cost of the voucher codes being handed out to customers who would have purchased anyway or had no intention of making more than one purchase.”
‍Jackie Barnett, Head of CRM at MandM Direct

Because generic email capture is a catch-all, it’s hard to work out what’s in it for the customer. Retailers resort to bribing visitors with discounts. This leads to a bad outcome: lost margin.

Offering discount codes in sitewide pop-ups might help you capture emails, but that’s because you’re giving money away to everyone by default. We’ve already explored the status quo of discounts in this article if you want more on the subject.

Fundamentally, generic email capture pop-ups cost you customer relationships, margins, and sales. But if this is the industry standard, what options do retailers really have?

Approaching discounts based on visitor intent

“Imagine someone is browsing sneakers, comparing a few models, maybe even checking delivery options. They’re clearly into it, but not quite ready. That’s when a “Hey! Want 10% off your first order?” feels helpful, not annoying. It’s like catching them at the right moment in-store, not shouting at them the second they walk in.”
Kardelen Ozyurda, UX & CRO Manager at PUMA

That’s the shift. Ask when it feels natural.

If you're not sure when these moments occur in your customer's online buying experience, consider when you might go over to a customer in a store setting to ask if they want more help, more information, or some material to take home. This exercise can also help you work out what to offer in return—whether that’s a newsletter, discount code, or a stock alert.

It should be obvious to the visitor why you need their email address, because there's value for both parties.

“We ask for push notification permissions after customers have done a 'high-value' action, like adding a product to their basket or purchasing. It's an easier value exchange when the customer can see the why behind giving their permission. We found the rate of acceptance skyrocketed when we did this.”
Alfie Calas, Head of CRM at thortful

If you find yourself cringing at the idea of only asking people at the end of the journey and not everyone, consider this: intent-based email capture reduces impressions by 50%. But it also grows sign-ups by 40%.

You know why?

Because it only triggers when appropriate.

“Context is everything. Email capture should be aligned with genuine value, like after engaging content, unlocking a discount, or adding to cart. The more it feels like a fair exchange, the better. The key is making it feel earned, not demanded.”
‍Niall Young O'Brien, CRM Manager at Represent

The more value you can convey, the higher the conversion rate of your email capture.

What’s wild is transforming something that actively annoys people into something that they are happy to sign up for, just by changing when you show it. It’s no longer one-sided.

What you say is just as important as when you ask. The more relevant what you say is to the individual, their mindset, and stage in the buying journey, the more likely you’re going to get your form filled in. Not only that, but relevancy has an added bonus when it comes to relationship building.

“Personalise the ask, tie it to behaviour, interest, or value. Relevance builds trust, trust builds lists. Ask when you’ve earned it. Timing + relevance = quality leads and higher conversion.”
Brad Ledson, Email Marketing & CRM Manager

Brad echoes what Jackie said earlier. Today's customers want, or even need, to trust the company asking for their information before they will give it away.

If you offer a discount for first-time buyers shortly after someone checks out as a guest, they aren’t going to have much faith in your brand. Likewise, if the visitor is in product research mode, offering a discount won't resonate as well as offering a handy guide to the product.

Retailers want relationships, not emails. But old tactics and poor tech haven’t kept up with how customers should be treated. The status quo prioritises capturing emails over customer experience and sales. To flip the script, retailers need to ask for emails at the right time in the right way, based on buyer intent.

Want to capture emails without subjecting your customers to generic, inappropriate pop-ups? Explore Email Capture with Intent.

Thanks again to all the ecommerce experts who shared their thoughts with us:

Jackie Barnett, Head of CRM at MandM Direct

Brenna Milleville, Founder at Elly and Grace

Natalia Lavrenenko, UGC manager/Marketing manager at Rathly

Alfie Calas, Head of CRM at thortful

Ben Read, CEO at Mercha

Asim Rahat, Founder at Oswin Hyde

Kardelen Ozyurda, UX & CRO Manager - Ecommerce Europe at PUMA

Niall Young O'Brien, CRM Manager at Represent

Brad Ledson, Email Marketing & CRM Manager

May 21, 2025

Intent-led solutions

How to get started with intent-based discounting

Throwing discount codes at everyone is costing more than it converts. Learn how intent-based discounting helps ecommerce brands protect margin and drive smarter conversions.

Charley Bader

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Read Time

Retailers aren’t discounting to be generous. They discount to drive conversion. But when you throw codes at everyone, all the time, it stops working. And, they’re not always needed.

Our Intent Gap report found 83% of online shoppers say they’ve used a discount code when they would have paid full price.

That’s not incremental revenue you’re gaining. That’s margin erosion.

Worse still, this catch-all approach conditions customers to expect a discount. Once they’ve had that 10% off, they’ll wait for it next time.

Shoppers aren’t fooled. They know the discount game. And they’re playing it better than most retailers. I’ve definitely logged in to my account, added some items to my basket and waited for that abandon basket email to come through. More than once.

But we’ve already covered the problem with the status quo of discounting, both from the ecommerce leader’s perspective and why we think intent changes things. This piece is about how to solve it.

To be clear. We’re not saying discounting needs to stop. But it does need to change.

Rethink: Why you’re discounting

Conversion rate matters. But it doesn’t tell the full story.

Of course if you give somebody a better deal they’re more likely to convert. So when it comes to the pros of discounting, we feel it’s smarter to be looking at metrics like:

Incremental revenue: Are you gaining additional purchases, or giving away a % to those you’d have had anyway?
Margin protection: Are discounts going to those who actually need them? Who wouldn’t purchase without?
Intent to purchase: Are you helping someone over the line, or just handing out money to all?

Most retailers discount too early, too often, and to too many people. The fix isn’t more codes. It’s smarter targeting.

So where do you start?

Rethink: Who you’re discounting

At Made With Intent, we use a framework that maps where a visitor is in their buying stage (Engage, Build, Maintain, Convert), and what behavioural signals they’re showing (Focused, Struggling, Abandoning).

That gives us 12 core intent-based segments. And not all of them need a discount.

Start with visitors in the Maintain or Convert stages who are showing signs of struggle or abandonment. These people have intent. You’re just helping them follow through on it when they signal they’re hesitating, or going to leave.

On the other side, visitors in earlier stages or those showing focus don’t need an incentive nudge (at least not yet!). Give them one, and you’re spending margin unnecessarily.

Once you know who to target, the next step is how and when to show the offer.

Optimise: 2 ways to start discounting with intent

You don’t need to build something new. Just optimise what you’re already doing. Once you’ve tightened your audience, it’s time to rethink your triggers and delivery.

Play 1: Trigger discounts for high-intent abandoning visitors

Most retailers show discounts on landing. Pop-ups fire after 30 seconds, three pages, or immediately. But these rules have nothing to do with actual buying behaviour, they’re just proxies.

Instead, you should look for visitors with purchase intent. Then wait for signs of abandonment. Only then do you trigger the offer. And deliver it to visitors directly on site - not through an email sign-up campaign.

Appliances Direct adopted this play and focused their incentives on the Convert Abandon segment, also known as visitors showing high intent but clear exit signals. By targeting only this segment, they saved 42% in margin while maintaining conversion rates. See how Appliances Direct did it.

Better Bathrooms also used this exact approach to great effect. By targeting Maintain Intent Abandon visitors showing hesitation on PDPs, they triggered context-aware discounts only when abandonment looked likely. The result? A 25.6% increase in conversion rate without widening the net. Read more about Better Bathrooms' approach.

Why does this work?

These visitors are already ready to buy, but something’s causing them not to
You reduce giving away unnecessary discounts to casual browsers
You create a smoother journey (no email sign-up delay, no inbox hunting for a code)

Besides, our Intent Gap report found 85% of online shoppers leave the site just to go find a discount code anyway. So either don’t make blanket offers, or don’t make them. Serve it when it matters instead.

Play 2: Offer timely incentives for struggling visitors

Not every visitor needs a discount. But some need a little help before they slip away.

While we recommend most retailers start by targeting Abandon signals, there’s a critical opportunity earlier in the journey. Struggling visitors. Our Maintain and Convert Struggle segments are shoppers who have shown clear intent, but are starting to lose confidence or momentum.

By detecting this behaviour in real-time, you can intervene. Either with the same promotional offer or a lighter-touch incentive, such as free delivery or even a lower-value discount.

These nudges help prevent drop-off before it turns into abandonment, while letting you reserve larger offers for those who really need them.

You can also factor in a visitor’s intent to return to site in the future. If someone is abandoning with high purchase intent but is unlikely to come back, you might want to push a stronger offer.

This is where the nuance of real-time intent shines. You’re not treating everyone the same. You’re responding with the right kind of support at the right time.

The core segments in our framework make these two plays possible with minimal effort. But the power of real-time intent data can take discount strategies even further.

Grow: What comes next

By this point, you’ve cut waste and improved impact. But what if you could push performance even further without giving away more?

Once you’ve refined your targeting and timing, the next stage is relevance and context. This is where Optimise starts becoming Grow.

Made With Intent lets you track affinities to products, categories, price points or brands based on rising purchase intent. You can use this to personalise the discount depending on visitor interests or your margin.

Seasalt Cornwall used this data to deliver category-based discounts only to visitors in the Maintain Abandon segment - those with clear product interest showing signs of hesitation. The result? An 89% uplift in conversion rate by focusing offers where they mattered most. Read the full Seasalt case study.

But this is just one way of interpreting it. Other examples include:

Varying the discount amount based on product margin (e.g. 20% off dresses, 5% off jewellery)
Offering an alternative incentive, such as free delivery on larger high-ticket goods, to further protect margin
Using copy that makes the discount feel personal (“Still thinking about that top? Here’s 10% off”)

Now you’re not just nudging in the right time and place, but with the right offer for them. Tailoring both incentive type and depth to how your visitors are behaving, and where they are in their journey.

This is where smarter discounting becomes smarter merchandising.

What happens when you get this right?

When intent-based discount works, you don’t see conversion drop. You see:

Stable conversion overall (because the people who don’t need a discount don’t miss it)
Higher conversion for those who do receive the discount
More incremental revenue and margin saved

You also build a better customer base. One that’s not hooked on the discount drug.

Discounting doesn’t have to feel like a trick. It can feel like understanding your visitor, and using the levers you have available to you.

Your first 3 steps

If you're looking to make an impact fast, here’s where to begin:

Replace early blanket discount pop-ups with intent-based triggers
Offer high-intent abandoning visitors a discount while they’re in-session
Intervene with high-intent struggling visitors, offering the same or a lighter incentive

From there, you should explore your segments further. Looking at affinity and intent to return data to identify the next priority.

This isn’t about giving more or even less discounts. It’s about giving smarter discounts, only when they make a difference.

Want to see how Made With Intent makes this possible? Get a demo of our real-time intent agent.

April 23, 2025

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Ecommerce expertise

The truth about CRO: Why metrics aren’t enough

David Mannheim

•

Read Time

CRO is a process, not an event

Do you know how the term “conversion rate” came to be? Like most things, it has an origin.

Bryan and Jeffery Eisenberg coined the term “conversion rate optimisation” in 1998, partly by serendipity, partly through intent.

Back in those days, it was a pre-problem, and so the category didn’t exist. The term “conversion rate” didn’t even exist, let alone optimise something that was non-existent. In fact, the only reason the search term even remotely appeared in Google was because people were searching for currency conversion rate, not website conversion rate.

“We knew conversion rate from sales was an important metric. We were always doing optimization and search optimization was growing as well. Conversion rate was a ranking term so we combined the two. We were writing about this and similar terms for years before anyone else was even talking about it” said Bryan, and so, they chose to rank for this - “conversion rate optimisation”. But, wrongly, with a Z instead of an S. Not using proper Queens English, I see.

Some say creating this term was nothing more than gaming the Google algorithm designed to create a business. But they were, rightly, trying to assimilate a term that described their efforts to grow businesses and support user experiences while doing so. Yet, their intent had an unexpected outcome.

Despite Bryan always citing that “conversion is a process, not an event,” the term conversion rate optimisation has since stuck. It has become popular amongst brands for its outcome and simplicity—too simple perhaps. It’s not just about optimising a single conversion rate, but the process of improving customer experience iteratively, ideally with validation.

CRO is an event, not a process

Yet, that’s not how people see it. Society sees the event, not the process. They see the 2% that converts, not the 98% that doesn’t. If you optimise the conversion rate, you inherently ignore the needs of the majority.

Is there a blame here? Most tend to lie fault with the definition, but I blame the metric. Seeing conversion rate as a metric or a measure of success is why it has failed us.

Fast-forward fifteen years from Bryan and Jeffery’s digital Frankenstein. In 2013, the confusion of optimising a conversion rate was evangelised further. Dan Barker wrote for Smart Insights on why conversion rate is a—quote—“horrible” metric to focus on. Horrible is an intense term, Dan.

The reasons are obvious: it’s aggregated, not controllable, and does not reflect true performance.

That won’t stop the blog posts from peddling conversion rate as an event with the likes of “What is the average conversion rate?” - the answer being 1.4% for all Shopify stores apparently [-]. Or “What is a good conversion rate? Lo and behold, it’s above 3.3%. Such irreverent content that lacks context; trying to aggregate a measure that varys from product, to device, to source, to demographic, to gender, to weather, to pay day to hour per day.

While conversion rate optimisation might be seen as an event, if you asked any conversion rate optimiser, no one will say they optimise conversion rates. They will talk about the process not the measure of success.

This is because today, experts and practitioners know that conversion rate optimisation involves what Bryan and Jeffery designed it to be, unfortunately, warped by the simplicity of society. For years, there have been movements in the CRO industry to reinvent the term. I’ve heard it all, from CX (customer experience), to GO (growth optimisation) to BGO (business growth optimisation). These calls are cries for help and this has been going on at conferences, in blogs, and podcasts for a long time yet never quite landed.

The common denominator? The removal of the term “conversion rate” and the disassociation of the event from the process.

Beyond conversion rates: Fostering genuine customer experience

Conversion rate optimisation fails us because it focuses on a metric—one that is, as Dan described it all those years ago, an aggregated, macro, uncontrollable, retrospective, binary measure of success that can easily be gamed.

Sure, we can increase a conversion rate - we could:

just reduce all prices by 10% or give free shipping for our first 5 orders. Done.
stop sending paid traffic to the website so that only those who know about us will visit. Completed.
only send desktop traffic to the site, never mobile. Obviously.
prioritise search results for our cheapest items. Next challenge.

See? Easy.

But can you grow something more meaningful? Something related to average order value? Dare I say, to customer satisfaction? To returning? To loyalty? Something that moves away from being a business KPI, a target to work towards, and more towards a genuine reflection of good user experience? This is what conversion rate optimisation should be.

The cobra effect

Pitfalls of conversion rate targeting: Lessons from Goodhart's Law

Instead of what it should be, and what is seen by experts all around the world, conversion rate optimisation’s success has morphed it into something else. It’s moved down the dwindling haunted road from a process to an event to a target.

When a measure becomes a target, it ceases to be a good measure

This is Goodhart’s Law.

It was a term coined in 1975 by none other than Mr. Goodhart suggesting that “Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes” [-]. Fun fact: it was later built upon to inform AI development in the Machine Intelligence Research Institute by a certain David Manheim. No relation [-].

This law is everywhere. In politics, if success is measured by approval ratings, it becomes a popularity contest rather than driving meaningful results. In GP patient admissions, success is determined by the number of appointments completed in a day; the quality of patient care might decrease as a result.

Yet there is no better reflection than the anecdotal and questionable validity of the “Cobra Effect” story.

Under British rule, the government was concerned about the number of venomous cobras in Delhi. So, they offered a bounty for every dead cobra, where large numbers of snakes were killed for the reward. Eventually, however, enterprising people began to breed cobras for the income. When the reward program was scrapped, cobra breeders set their now-worthless snakes free, the wild cobra population further increased [-].

Conversion rates are our cobras. Where, instead of cobra-breeders, we have pop-up breeders.

Continuous optimisation towards a single measure - sorry, target - pushing users down a cul-de-sac of “please convert today”. Don’t lie, we’ve all experienced the “10% off now” pop-up shoved in our face as soon as we land on most sites. Inappropriate behaviours caused by inappropriate targets creating this myopic form of digital directness.

In short, how brands measure directly reflects how they sell. And currently, they sell to do nothing but convert.

How do we solve this?

If the problems of conversion rate optimisation, are that it aims towards a target of something that is macro, binary and out of your control, it makes sense to focus on a measure of success that is micro, scaleable, and controllable.

Towards metrics that are micro, yet specific.

The concept of treating every customer the same is silly. It sounds silly. It feels silly. Everything becomes the same because brands treat everyone the same. This manifests itself in how brands currently measure success on websites: using conversion rate.

The metric used to understand success is highly aggregated at a macro level. It’s an average of averages of averages. It’s made up of so many conversion rates (plural) that trying to shift that behemoth metric is akin to pulling a U-turn on the Titanic – it’s going to take a lot more than a boatload of topless coal trimmers.

The result of optimising for an averaged metric is an averaged approach. The result of optimising with an averaged approach is an average result. Homogenisation begets homogenisation.

Much to Goodhart’s law, by optimising metrics that are aggregated, the output, too, becomes aggregated. It is why in ecommerce that we see page template optimisation based on the homepage, the product listing page, followed by the product detailed page, then the basket and finally the checkout.

A true enemy of personalisation.

The king of which, Netflix, announced as of 2024, they will no longer report on its average revenue per member (ARM), believing this is an irrelevant statistic to measure success. [-] They cite it being an irrelevant measure due to its macro view of what it indicates; the clue is in the name average revenue per member, one that holds so much volatility over a period of time

It’s also a measure of success that’s indicative of business performance, not necessarily customer performance. Sorry, averaged business performance, not average customer performance. And so, moving towards something more symbolic of customer satisfaction, like viewing time, is a movement towards a move away from the macro aggregation of a one-way business metric and towards a measure that highlights the specificity of the business model.

Towards metrics that demonstrate scale and momentum

Conversion is not a binary point of success or failure. It is a progression of performance. A momentum.

As a brand, my job is to build customer momentum, persuade, create desire and elicit these emotions to allow you, the user, to take action. It’s not to just go straight for the jugular or to flip a switch.

And yet - why is it measured as such? There’s a reason why the majority of marketing models have a funnel usually in the form of four letters that tenuously spell out a loosely put-together acronym: the AIDAs, REANs, ACCAs all stand up.

Put somewhat more succinctly, the process of buying online is about an upward trajectory not an end outcome. Translated into KPIs, it’s about scalable performance, not a binary result.

Looking at a not-so-similar industry, we can see what changing the success metric did for the world of football (he writes as Germany are battering Scotland in the Euros). Expected Goals (xG) was a stat created by Opta for use in football. A metric that indicates the quality and performance of the game based on a series of attributes fused together. These might include the angle of a shot, possession of play beforehand, the distance of a shot, and; less so who is taking the shot. It “provides an antidote to the disease of randomness which permeates football” (Tippett). Sounds familiar. In other words, it’s a statistic that is better representative of 90 minutes of a game than just what might be a lucky 5-1 win (granted, Germany isn’t lucky in this game). It’s a statistic that helps understand the performance of the game, not the end result.

Like ecommerce - still, unfortunately - football is built on opinion. OK, that’s what makes it fun. But, the data revolution requires more rigour when commercials are at stake.

Online needs to move towards something more indicative of movement, momentum, performance, quality, and play, less so the binary outcome of whether someone did or didn’t do something. This metric should be one that scales as behaviour does.

Towards metrics that are within your control

Conversion rate is not entirely within your control. If you’re selling umbrellas and it’s sunny, guess what will happen to your conversion rate? It’ll get rained on. The adverse, too, if it rains, the sun will ironically shine on sales.

There are far too many uncontrollable factors to determine whether someone will or will not do something online. When you put it like that, it makes it kind of silly that we look at conversion rate as a measure of success for websites now, doesn’t it?

In the 90s, Donald Wheeler wrote about “the key to managing chaos” and spoke directly about casual relationships. Specifically, “You cannot improve by listening to the voice of the customer. You can only improve a process by listening to the voice of the process”[-].

These are fancy terms to suggest that focusing on the result—a demand from the customer or management—is not nearly as impactful as understanding how the process actually works: casual relationships.

Losing weight is a great example. You are in control of the inputs or calories in and calories out. If you understand how those inputs impact the result, your weight loss process, you will lose more weight. Of course, there are plenty of inputs within each primary input—the balance of carbohydrates, protein and fats, water intake, type of calorie—I could go on, but I’ve clearly not lost much weight in over 12 months.

This is a reason why Amazon only measures success on what they can control, and what they input; something talked about in great detail under Working Backwards [-]. The calories in and the calories out of ecommerce—not the weight loss. This might look like (and does in accordance with Amazon’s WBRs - Weekly Business Review):

An increase in the number of detail pages, while seeming to improve selection, did not produce a rise in sales; the output metric
the percentage of detail page views where the products were in stock and immediately ready for two-day shipping, which ended up being called Fast Track In Stock, did produce a rise in sales, the output metric

These are written as hypothesis in alignment with their ruthless test and learn culture at Amazon, but the principle remains: Focus on the input, not the output. This will prevent a Goodhart’s Law type of situation.

Towards intent metrics

If the micro beats macro.

If the demonstration of measures that scale beats an outcome that is binary.

If controllable inputs beats uncontrollable outputs.

We need a measure that is reflective of the nuances (micro measures of success) of the performance (the scaleable momentum shifts) of a user (not the business); not just the end outcome.

We took great inspiration from the Germany-Scotland game and created a measure that helps understand the quality of the play as opposed to the quantity of the outcome. A sentence that permeates the world in “quality beats quantity,” which, if you stand behind, will almost certainly have you sitting on the edge of your seat for this one.

Introducing Intent.

We collect 250x different intent signals—the nuanced behaviour of what users do online—and model those together, outputting them in a series of predictive metrics.

Breaking these metrics down into the known metrics with a predictive layer, we find:

expected conversion (xC) - the likelihood that a user will convert
expected add to cart (xATB) - the likelihood that a user will add to their cart.

From there, at Made With Intent, we utilise metrics indicative of behaviour that are more brought forward than the macro level.

expected exit (xE) - the likelihood that a user will exit their session
expected return(xR) - the likelihood that a user will return to the site.

And finally, we land on a measure that helps understand the core of what selling is all about: nurturing.

expected progression (xP) - the likelihood that users will progress to the next stage of the buying journey. We call these “buying stages” and identify them as browsing, refining, evaluating, deciding and committing. They are also similar to those 4-letter, 1980s acronyms thought up by genius marketers.

Not to mention in all of these, the benefit of these being expected measures. One of the consistent flaws of conversion rate is that it is a retrospective target. A measure that’s already happened, and so, not something that you can influence there and then. Intent metrics have the added benefit of being predictive. They highlight what a customer might do, not something they’ve just done, meaning you can intervene in real time. Whilst predictive analytics was on the rise - at the peak of expectations in 2018 [-]- their use cases in ecommerce have been limited. The introduction of real-time analytics has brought this somewhat to life, in combination with using first-principle thinking (thank you, Germany vs Scotland).

Conclusion & next steps

When Netflix announced a move away from reporting on subscriber growth to something more indicative of success, they used two words in their shareholder letter that were the most vital of the announcement: “We’ve evolved”.

Ecommerce needs to evolve.

The flaws within conversion rate are evident for all to see. It is an aggregated, macro, uncontrollable, retrospective, binary measure of success that can easily be gamed, where optimising reflects how you will sell. Cue the 10% off popups as soon as someone lands on your site.

The introduction of Intent metrics is a movement towards the opposite. It is a reflection of the performance, not just the result. An appreciation of the progression and momentum build of prospects, not just a binary outcome. A systematic approach to identifying controllable inputs as opposed to reviewing the uncontrollable outputs. Most of all, it is a focus on the predictive, not the retrospective.

July 22, 2024

Intent-led solutions

Online discounting: A race to the bottom or a strategic ecommerce growth lever?

Colin Spooner

•

Read Time

The ecommerce landscape has evolved dramatically over the past decade. Technological advancements, shifts in customer behaviour, and global events like the COVID-19 pandemic have accelerated online retail.

An estimated 24 million online stores worldwide compete for attention and spending. Platforms like Shopify and WooCommerce have simplified online retail, empowering entrepreneurs and established brands to establish their digital presence.

But a significant challenge bubbles underneath all this progress: competitive advantage through pricing strategies—a race to the bottom.

In this race, profit margins are sacrificed in favour of cutting prices to stay relevant and keep conversions high. Unfortunate side effects like eroding brand value and conditioning customers to expect discounts as the norm have been accepted at the price we pay to play.

For many ecommerce brands, this has become a dangerous balancing act: how to drive sales without compromising profitability or brand integrity.

But there are ways to leverage discounting, not as a desperate measure but as a strategic growth lever.

You can enhance customer satisfaction and loyalty by tailoring discounts to customer behaviours while safeguarding profit margins.

In this article, we’ll explore the challenges ecommerce retailers face with traditional discounting strategies, examine segmenting and targeting your audience effectively and discuss the impact of strategic discounting on brand perception and profitability.

Protecting your margin

The problem

The cost of goods is skyrocketing
Prices are constantly under pressure due to intense market competition
Brands feel compelled to sacrifice margins to maintain or grow market share through widespread discounting

Discounts can give an immediate boost to sales figures, but often don’t contribute to sustainable growth. They merely accelerate revenue to meet short-term goals.

The solution

Implementing a real-time segmentation framework.

Their current state (whether focused, struggling, or abandoning), and most crucially, their intent, tells you when to step in and offer a discount or whether you can safely stay out of your customer’s way and allow them to purchase.

By segmenting your audience based on these stages, you can identify where customers stand in their buying journey, allowing you to make more appropriate offers.

This segmentation can be integrated into on-site discounting strategies and CRM platforms for managing discounts in behavioural campaigns like abandoned cart communications.

As an example, customers showing focused behaviour with a high intent to purchase may not need discounts to convert. In such cases, retailers can opt to hide or reduce discounts, preserving margins and focusing on opportunities for incremental sales.

By strategically understanding customer intent, ecommerce brands can steer clear of the race-to-the-bottom mindset prevalent in the market.

This approach ensures profitability while still meeting customer needs effectively.

Protecting your brand

The problem

Online retail competition intensifies
Retailers increasingly rely on promotions
Constant and widespread discounting
Brands are trapped in a cycle of perpetual discounts to outdo previous campaigns

Over-reliance on discounts damages brand perception. Many customers now question the authenticity of pricing and categorise some brands as “discount retailers.”

This shift in customer perception threatens brand reputation, especially for retailers focused on quality and higher price points, threatening their long-term growth.

The solution

Discounting based on intent to purchase.

The issue isn’t discounting itself but how we execute it. Generic and blanket discounting strategies need to be replaced with strategic discounting reserved for those who actually need it.

Pinpoint where customers are in their buying journey precisely—whether they’re engaged, hesitating, or at risk of abandoning their carts—and, crucially, their purchasing intent.

Use real-time behavioural data to offer discounts only to those showing low intent, are struggling, or highly likely to abandon. Strategically deploy discounts to these specific customer segments at the right moments.

This approach reduces discounting noise, protects brand perception, and responsibly uses discounts as a strategic tool for sustainable growth.

By demonstrating a nuanced understanding of customer preferences and needs, you can not only meet immediate sales goals but also build trust and foster loyalty.

Discount smarter, not harder

Whether you’re protecting margins or brand reputation, it’s clear ecommerce is stuck in a cycle of dysfunctional discounting.

Effective discounting isn’t just about slashing prices randomly; it’s about timing and relevance.

You need a game plan that identifies where customers are in their buying journey and whether they’re keen to buy or still window-shopping.

Instead, tap into intent data to figure out who needs that little nudge and when.

Segments for discounting

Here are a few segments you can implement to identify those that might need a helping nudge.

Basket Pauser

Context: Abandon behaviour
Summary: These customers have built up a basket and are now showing signs that they’re likely to leave and may return
Objective: Maintain Intent. What can you do to encourage this behaviour, e.g., save items for later (with email), sign up for payday reminders, etc., or convince these customers that now is the right time to purchase?

Basket Abandoners

Context: Abandon behaviour and unlikely to return
Summary: These customers have built up a basket and are now showing signs that they’re likely to leave and not return
Objective: Maintain Intent. This is likely one of the last chances you have to persuade these customers; think about appropriate messaging that can reduce their likelihood of exit. This is the perfect segment for you to highlight immediate value. It’s extra time, and it’s probably your last-ditch attempt to keep them and persuade them to convert.

Struggling Buyers

Context: Struggle
Summary: Customers likely on the checkout who are showing struggle behaviours
Objective: Convert. They’re struggling and not checking out. Why? Are they checking discounts? Rather than push them through a checkout when you know this journey isn’t typical, how can you allow for the fact that they don’t seem ready to buy? Without cutting the checkout off, of course. Understanding and addressing this hesitancy is key to converting stalled checkouts into successful transactions.

Hesitant Buyers

Context: Struggling, not in Committing
Summary: Customers who showed they are ready to convert but are no longer on the checkout and who are showing struggling behaviours
Objective: Convert. The challenge with this segment is understanding and addressing the underlying anxieties that hold them back. That can be a set of questions you’re not answering effectively enough, concerns about the product, price, and trust in the brand. How can you influence their experience to remove any anxieties causing hesitation and promote motivating factors?

Last Chancers

Context: Abandon, low expected return
Summary: Customers who showed signs they wanted to convert but are now abandoning the journey and are unlikely to return
Objective: Convert. These customers have demonstrated high levels of intent but are unlikely to return and are predicted to exit soon. This is likely one of the last chances you have to persuade these customers; think about appropriate messaging that can be used to reduce their likelihood of exiting. This is the perfect segment for you to highlight immediate value. It’s extra time and probably your last-ditch attempt to keep them and persuade them to convert.

Segments to avoid discounting

Here are some segments that might not need a discount, but may need other nudges instead.

Unengaged Browsers

Context: Struggle Behaviour with active events in Browsing (min. 10 events)
Summary: These customers are starting to interact with the website, but they’re not progressing from browsing and actively engaging in product discovery (yet). Unengaged Browsers are characterised by their lack of interaction beyond basic page views.
Objective: Engaging this segment means understanding why they’re hesitating, piquing interest and encouraging a deeper exploration of your site. Inspire these customers with categories/products to help progress them in their journey. They interact with the website but haven’t moved into a Refining Buying Stage.

Basket Convincers

Context: On a PDP with a high affinity for the current product but has not yet added to the basket
Summary: These customers are on a PDP, with a strong affinity for the product they’re looking at and high Add to Basket activity, but they have not yet added any items to the basket
Objective: Build Intent. How can these customers be convinced to Add to Basket? Consider product-specific anxieties and motivators that can be used to influence them. They need just the right nudge to transition from interest to action. The challenge lies in identifying and addressing the factors that can convert this hesitation into decisive action.

Struggling Evaluators

Context: Customers who haven’t added a product to the basket, have viewed multiple PDPs and haven’t built an affinity for any products
Summary: Broad Evaluators are the *tire-kickers*. They are shoppers immersed in the evaluation stage, showing an interest in what your brand offers but without any clear direction or behaviour towards purchase.
Objective: Build Intent. The objective is to guide deeper engagement with your brand first and then your products, not the other way around. They need help finding the right product. They need ease of comparison but also content to help them understand what product is right for their needs.

Product Persuaders

Context: Showing struggle behaviours, haven’t added any products to cart, have built product affinity/affinities but are losing momentum
Summary: Customers who have built a product affinity but have not added any items to the basket and whose journey is showing signs of slowing down / heading in the wrong direction
Objective: Build Intent. Their behaviour suggests a moment of hesitation or reconsideration. They have potential interest in specific products or categories but also need further persuasion or reassurance. How can you help these customers get back to a product and persuade them to actually add to basket?

Focused Shoppers

Context: Positive behaviours
Summary: These shoppers are on the cusp of conversion, are progressing nicely and are making their final decision(s) before moving to checkout
Objective: Maintain Intent. Keep these customers on track (probably just leave them alone or use subtle enhancements to the journey), and if needed, help move them into checkout. Make things more accessible, and gently persuade them over the finish line.

Ready Returners

Context: Landed back on site (at least 2nd session) and have a high likelihood of committing
Summary: Landing page customers who have returned to the site and, after showing high intent to purchase, are likely back to purchase again.
Objective: Maintain Intent. Their behaviour is a testament to their previous unresolved actions. Having already shown high levels of engagement, the challenge now lies in nudging them over the final hurdle to complete their purchase. Try to understand why this behaviour exists. How can you get these customers back into their product purchase journey without distracting them when they return?

Embracing change for sustainable growth

You don’t have to get trapped in that discounting death spiral - it’s possible to use discounting as a strategic tool.

Understanding customer intent allows you to be hyper-targeted with your discounting, protecting your margin and elevating your brand reputation.

Dig deeper into our intent-based segmentation framework here, or get into some execution strategies for making discounting work harder.

Here’s to shaping the future of discounting—one smart discount at a time.

July 16, 2024

Intent-led solutions

Data insights: Pop-ups, timing, and Intent

Colin Spooner

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Read Time

Pop-ups. Seen as the noisy, uninvited guests of the digital world by customers and a tool for list growth and revenue generation by ecommerce teams.

In the race for conversion, many ecommerce sites bombard visitors with pop-ups from the get-go, hoping sheer volume will lead to clicks and sales.

This “more is more” attitude often results in visitors reflexively closing pop-ups in irritation and possibly abandoning the site altogether.

Pop-ups can boost engagement and conversion rates when used effectively, but they often miss the mark.

Key takeaways

Pop-up success relies on careful timing

Data shows pop-ups are most useful at evaluation stages. Our LLM data shows that pop-ups in the sample were most effective during evaluation for the loyalty campaigns being run.
Pop-ups shown too early get ignored. When triggered too early, such as during browsing stages, pop-ups we closed without action taken.
Contextual nudges can maximise conversions. Nudges can significantly boost conversions when they’re used in conjunction with intent.

Let’s dive in.

The pop-up pitfall

Ignoring Intent

Many ecommerce teams focus on showing pop-ups to a broad audience early in the customer’s journey.

This rush for conversions often leads to visitors automatically closing pop-ups without reading them.

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Pop-ups should be paired with an understanding of customer intent, only displayed for segments of your audience that need the additional nudge.

To avoid the use of pointless pop-ups, we must provide them to visitors when they’re most receptive.

By leveraging intent data, we can pinpoint the exact stage and intent level where visitors are most likely to engage with a pop-up.

Loyalty program pop-up

The early bird gets... ignored?

Analysing the data for a series of loyalty programs, we tracked the display of pop-ups offering points for spending more.

Despite the attractive offer, 98.5% of visitors ignored the pop-ups because it appeared too early—during the browsing stage.

However, when shown during the evaluating stage, visitors were 71% more likely to engage, highlighting the importance of timing and intent.

Though the number of visitors at the evaluation stage varies, analysing this data helps find the best triggers and timings for pop-ups.

These pop-ups are crucial in influencing the buying journey, so it’s essential to show them at the right moments to effectively engage visitors on the site.

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The role of nudges

Conversion optimisation

Nudges, like pop-ups, are key for guiding visitors toward buying by providing important information.

Visitors who see too many pop-ups too early can be overwhelmed and driven away. Instead, spreading personalised information throughout their journey can make a big difference.

Case in point

Digging into the data, an experiment with nudges around product/service USPs based on intent levels saw conversion rate jump by 20% (US) & 44% (UK).

Aligning pop-ups and nudges with the visitors’ buying stage and intent boosted engagement and conversion rates.

Instead of showing pop-ups to all users right away, a more targeted strategy delivers better results.

Actionable tips

Implementing an intent-based pop-up strategy

Analyse Intent: Use analytics tools to gauge your visitors’ intent level and buying stage when interacting with your pop-ups and nudges.
Tailor Pop-Ups: Customise pop-ups to appear at the most appropriate journey stage, reflecting their intent.
Test and Optimise: Continuously test and refine the timing and content of your pop-ups to maximise engagement.

Recommended tools and resources

Google Analytics 4 (GA4): Track visitor behaviour and intent to refine your pop-up strategy.
Google Tag Manager (GTM): Set up tracking for your current pop-ups and include intent data as parameters, allowing you to analyse the data in GA4.

Pop-ups can be a useful tool to leverage engagement and interception strategies.

When timed right and aligned with intent, they can enhance the buyer journey and boost conversions.

By respecting the buyer journey and offering value at the perfect moments, pop-ups can transition from a source of frustration into tools for success.

July 8, 2024

Product news

Made With Intent raises £1.5m to put customer intent at the heart of ecommerce

Daniel Gripton

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MANCHESTER, 02/05/24 - Made With Intent have raised £1.5m to bring their segmentation platform and their vision for more appropriate eCommerce to market. Led by Mercuri, with Portfolio Ventures and previous investors Haatch following, the seed funding will support the fully remote team of 15 with their product, marketing and partnership efforts.

The idea came after the founder, David Mannheim, recognised a fundamental flaw in online retail strategies. After 15 years of optimising conversion rates in eCommerce, he realised the industry’s fixation on conversion metrics was the very thing holding it back.

“The current measures of success are the problem. Metrics like conversion rate, and therefore the actions retailers take to improve them, are short-term, retrospective and aggregated,” David explains. “This creates a race to the bottom. A numbers game that forgets how people really buy.”

Made With Intent looks to change this by giving retailers two things—a more human, segmented perspective of their website performance and a predictive targeting mechanism that lets other marketing tech respond to customer needs in real time. The company reports this new intent-based approach creates a 9.4% average revenue uplift compared to generic optimisation.

“eCommerce is often guilty of trying to convert all customers at all times,” David states. “It focuses on the minority who are ready to buy, at the expense of those who are not. Our product helps retailers be appropriate for every customer. To progress both in-market and future buyers.”

The Beta launched in September has already helped customers like Ernest Jones, Bensons for Beds and Rapha align how they sell with actual buying behaviours. Nik Fletcher, Head of Digital Experience at Rapha, describes the product as “the closest we can get to understanding subconscious visitor signals, like we can in a physical store.”

The platform works by collecting data through an easy to implement script, modelling 250+ signals from online shoppers and returning predictive intent metrics in real time. Visitors are then automatically segmented based on their journey, momentum and how likely they are to buy, exit or return in the future.

This data and the targeting of segments are handled in platform, but the tool is designed to be complementary. With integrations to 40+ marketing tools, from ad networks to experience tools and CRMs, eCommerce teams can use Made With Intent to deliver more appropriate shopping experiences or reengagement tactics with the tools they already use.

“Made With Intent has embraced first-principle thinking and a decade of insights to shake up the vast eCommerce market,” comments Alan Hudson, Founding General Partner at Mercuri. “It empowers online commerce, making it more personal and focused on the quality of prospective customers. The product roadmap excites us and, importantly, those using it.”

“As a VC investor we look at a vast number of potential investments each year, however we only invest in less than a dozen. Made With Intent's strategy is similar for its customers - to focus on the quality of the prospect, not the number of prospects."

With an existing user base in the UK, Denmark, Germany and the USA, the company aims to reach 100 global customers within two years. David Mannheim adds, "Made With Intent is about more than a platform. It's about a movement to create a more personal, human eCommerce. This investment brings us closer to fulfilling our mission."

For media or product enquiries please contact Daniel Gripton, VP Marketing, on LinkedIn.

May 2, 2024