Although we predominantly use Heap for our product analytics, over the last few months we've seen the benefit in using Heap data to answer business problems outside of the Product team and consequently we’ve worked hard to roll it out to other teams. Below is a summary of the questions asked by our Range, Data Science and Trading teams and how we used Heap to answer those questions.
Range
The Range team manage our collection, they work with the florists to curate the range and explore new product opportunities.
Questions they ask:
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How are our SKUs performing?
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Which ones should we bring back for next year?
How we used Heap to answer the questions:
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We look at a range of metrics to help us answer this question from SKU mix to NPS scores to resend/refund rates to understand how our SKUs are performing.
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The position of the SKU within the product listing page has a big impact on SKU conversion and thus the SKU mix. We, therefore, are able to use heap to calculate impression to order CVR per SKU which gives us an indication of true popularity.
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Together with the other metrics the Range team are then better informed to make a decision on the performance of different SKUs and are thus able to use this insight to plan for next year’s range.
Data Science
The data scientist team helps to transform all our data into usable intelligence. They build the Machine Learning and Artificial Intelligence (AI) solutions that help us solve problems at scale.
Questions they ask:
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How are our personalised machine learning models behaving?
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How can we generate new features to further enhance our models?
How we use Heap to answer the questions:
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Evaluate the machine learning models with metrics that are directly tied to the user experience.
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Use Heap to log all products seen and interacted with by a user, which means we can measure how well our product ranking models work to then work on further optimisation.
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Provides data to create dashboards to inspect what our users are actually seeing in their browsers and apps.
Trading
The Trading teams ensure we are trading effectively to hit our business targets and therefore are interesting in looking for and identifying ways to improve conversion and reduce wastage.
Questions they wanted answered:
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How can we optimise for conversion?
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How do we help customers find the products that they want?
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How do we highlight the wide range of products available?
How we used Heap to answer the questions:
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We were able to understand how customers navigate around the website/app and from this we were able to build recommendations on how to improve the navigation - removing sub-navs with low engagement and re-ordering the nav based on cvr.
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We were also able to analyse the performance of new ranges to understand whether curated navs achieve the mission to inspire.
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By looking at the various navigation features we are able to provide tailored insights by device type to really enhance the customer’s browsing experience.
Teams across my company have gained valuable insights from the web and app data we collect in Heap. I’d like to hear from others on how their teams use Heap and how you helped make it easier for them to adopt. Please add your thoughts in the comments below!