黑料大事记

Customer Intent for eCommerce

More human selling for data-led retailers

For retailers who require a new perspective. Who want to care for their customers. Who need a competitive edge. This is Moneyball for eCommerce. This is for you.

Intent is for those who know eCommerce can be better.

And we鈥檙e delighted to be building it. Not only because our livelihoods depend on it, but because we鈥檝e made something that makes online retail more personal for customers and more profitable for retailers.

Since starting this product (and for many years previous) we鈥檝e worked with retailers of all sizes and noticed a common problem.

In online retail, we鈥檝e fallen for a form of digital directness.

We鈥檝e forgotten how to sell like humans in favour of pushing for a quick buck. We鈥檝e digitised the shopping process, but also made lots of things about it cold or binary.

But people don鈥檛 work this way. Buying doesn鈥檛 work this way. So when retailers work this way, they limit the number of people who will purchase from them. In particular it:

  • Prioritises website pages over buying stages
  • Leads retailers to focus on the conversion and not the person
  • Forgets most customers are not ready to buy right now

To provide a better experience and reap the rewards, eCommerce needs to move from this digital directness to something more personal. Something more appropriate.

And we do this by doing what any good salesperson would do鈥攂y focusing on our customers and their intent. By predicting where people are on their purchase journey and treating them accordingly.

But doing this in online retail hasn鈥檛 been easy. It鈥檚 required data, engineering and design resources that only the leading teams have access to. It鈥檚 also been hard to know where to start, making it hard to dedicate already stretched time to.

Well, until now. Because this is what we鈥檝e made. A platform to help retailers understand and target customer intent.

We鈥檙e building Intent for the people who feel the same as us鈥攁nd the businesses that are lucky enough to employ them.

Best for...
  • Online retailers with >拢1m turnover
  • Teams with customer analytics
  • More considered purchases (we think)
  • People who want to personalise...
  • ...but don鈥檛 know where to start.
Not for...
  • Humungous or early-days retailers
  • Teams who have no data maturity...
  • ...or have a packed data science dept
  • Brands who don鈥檛 mind inefficiencies
  • People who are ok being impersonal.

Have a department in mind? We've Got You

Optimise your digital strategy

Give your retail business an edge that others overlook. Use customer intent to gain in-quarter sales, future revenue and a framework that scales.

How eCommerce leaders use Intent
Adapt your store for each user

Improve conversion rate and user satisfaction. Optimise your store experience by focusing on customer buying stages, not just pages.

How Experience teams use Intent
Engage by buying stage

Make your messaging more appropriate by knowing which customers need nurturing or nudging. Repeat orders and LTV gains await.

How CRM teams use Intent
Target purchase intent

Focus your time and budget on likely buyers. Increase your ROAS, decrease your CPA and be more appropriate in your digital marketing.

How Digital Marketing teams use Intent
Respond to visitors in real time

Add a predictive lens to your online store. Prioritise appropriate trading levers based on customer intent and impact on revenue.

How Trading teams use Intent

Why Ecommerce teams Love intent

Unlock Customer Intent for your ecommerce business

Just use the button below to register your interest.

Book a demo
What tech do I need to have to use Intent?

If you have an eCommerce site and an analytics platform, you don鈥檛 need anything else to get value from our product.鈥↖t complements analytics platforms like Google Analytics as it can add richness to user data. It complements AB testing tools as it can provide the context and the triggers for an experiment. It can even complement your existing CDP or CRM, as any data can be passed through via custom dimensions and variables.

What is the size of the Intent script? Does it impact Core Web Vitals?

The 黑料大事记 script is <10kb and has minimal if any impact on Core Web Vitals. While an impact is possible (as it is with any script ever) the impact of our script can be minimised easily with async or deferred script loading.

Can Intent data be used in other platforms?

Yes. All the behaviours and metrics we track, including our Expected Metrics, can be pulled into your existing tech stack. This includes any analytics, CDP or system that allows custom dimensions and variables. This also opens up a whole host of possibilities, from social ads and remarketing to email personalisation.

How easy is it to use the data? Can I use it in other tools?

In short, very and yes. We鈥檝e designed our product to always make our data easy to action. We don鈥檛 want to just be another 鈥榠nsights鈥 tool. Our segment creator is built into our analytics, making the valuable opportunities you find without your customer base actionable with the click of a button.

Once saved, a segment can be tracked but also targeted. Targeting starts by setting up triggers using our simple, self-serve menu. This whole process can be completed in the Intent frontend or via integration with your CDP or personalisation platform of choice.

Does Intent really work from a single script?

Yes, and you can get it all set up in less than 30 minutes. All you need to do to get setup is add our script to your site or tag management solution, such as Google Tag Manager.

Set up

1 Line of Code

Seriously. Our tiny script has no impact on your Core Web Vitals and tracks everything you need.

Privacy

0 Personal Data

We listen to every micro-interaction and use local storage, without extra cookies or GDPR concerns.

Compatibility

40+ integrations

Our data and triggers work with testing tools, experience engines, ad networks, email campaigns, analytics platforms, CDPs and more.

Accuracy

1 bn+ interactions

Our model is trained on over 50+ eCommerce websites, increasing model accuracy by >20%.

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