4 e-commerce experts share their diverse perspectives on digital analytics’ role in e-retail strategy. Hear the challenges they’ve face related to conversion optimisation, and get recommendations for driving e-commerce performance more efficiently thanks to data.
Webmarketing & e-commerce expert
Analytics is the common thread of custom webmarketing strategies
The online merchant’s challenge is to deliver the right message via the right channel with the right frequency, and to the right customer… and this challenge is even more complex as digital marketing costs have soared in recent years. Analytics data lets us refine our understanding of the customer journey in order to grow our acquisition ROI, provide relevant offerings, and boost customer satisfaction. Cart abandonment is one of the first issues e-retailers work on when they start with data analysis. Major CMS offer modules for sending emails that remind users if the product is still in stock, or to promote a deal that will motivate them to purchase. Though these actions are generally said to boost turnover by 10% on average, I think this figure should be weighted according to type of customer. I’ll share a striking example from my time at Perles & Co, a costume jewellery creation company: Analytics data allowed us to avoid “harassing” our very best clients.😊 More than 30% of our customers took longer than 20 days to finalise their cart. Without this understanding gained via segmenting the behaviours of our customer base, a cart abandon strategy that was too aggressive could have been a real disaster.
Digital analytics therefore allows us to adopt a custom webmarketing strategy. There’s no secret formula for having a winning e-commerce strategy: It’s all about knowing your personas and taking a real “test & learn” approach. Digital analytics also enables us to identify any bottlenecks in the purchase funnel and improve the way our product catalogue is organised (analysis of keywords searched on site, page bounce rate, product page conversion rate, etc.).
In terms of KPIs, customer lifetime value is a top indicator for us when calculating the ROI of our acquisition strategies. Nonetheless, many small e-retailers don’t have the internal resources to establish this indicator, and/or don’t want to invest in the tools needed to study customer lifetime value.
I therefore recommend categorising based on customer needs, creating clear product pages with 360-degree images, and ideally, using videos which really help stage the product or service. Reassuring elements (reviews from other customers, secure payments, shipping methods, etc.) are also very important.
CEO of mobibot.io
Give customers a real reason to (re)engage with you
Customers use many touchpoints before buying. The most efficient way to understand how modes of consumption are evolving is evidently with analytics tracking. With that said, being able to reconstruct the full customer journey is today more of a vain wish than a reality. Knowing if the customer has already seen the product before making an in-person visit to the store would enable the salesperson to better target his/her arguments and to know how far along the customer is in his/her purchase decision. Is the customer looking for advice? Recommendations? Or to simply confirm that the purchase is the right one?
I recall one of my clients who wanted to improve his conversion rate, which was 2 or 3 times lower than the average for a certain browser/system pair (Safari/OSX). After performing an extensive technical analysis, we identified that one of the JS files was not loading correctly and was affecting navigation in the funnel for a portion of visitors. Without the analytics data, it would have been impossible to notice this issue.
With e-commerce, the conversion rate obviously depends on your activity sector. For “impulse buy” products, a visit-based conversion rate can be useful. For more complex products, or for products that require longer consideration, one should instead take a visitor-based approach when measuring conversion rate. Generally speaking, there’s not just ONE conversion rate per site. I believe it’s useful to split up conversion rate into several sub-elements depending on your goals: by customer cohort, by browser, by device, by time of day, by product category… If you only study a single conversion rate, you risk not being able to truly leverage your data.
Regarding cart abandonment, we often think Internet users have voluntarily chosen to abandon their carts. This isn’t always true. We tend to underestimate the technical problems (problems on the site, payment issues, 3D secure issues, display issues, poor technical compatibility, refused payments…). A cart reminder system via email, for example, could be a way of winning back visitors who had a problem or who are hesitating. This is indeed a must-have in 2018. While ad retargeting should obviously be tested to see if it can reduce abandons, don’t forget the fundamentals:
Allow users to test several bank cards on a payment, use a specific cart URL which can be shared across mobile and desktop screens, for example, ensure your site is fast during the checkout funnel, offer a system of guest checkout, etc.
Regarding customer loyalty, I find the common approach often very technical. We often aim to create loyalty via our pricing (but in my view, this is not loyalty). To engage (or re-engage) customers, you must give them a reason. And to reference Simon Sinek, I’d say: no reason, no engagement, just a bit of opportunism at best.
Senior UX Designer and founder of Stash
It’s vital to measure conversion per user and integrate all touchpoints
Analytics data should be complemented with behavioural data (from Hotjar, for example) and with qualitative methods like user tests to better understand and address customer behaviour. There are 2 major moments in which analytics is essential:
– Upstream of tests, to help build personas, analyse and audit user paths, …
– Downstream of tests, to track results of the recommended actions and enable continuous improvements
At the conversion level, in certain industries such as tourism, the user journey is much more complex than just “simple” visits to a site. Unfortunately, we don’t sufficiently consider the other touchpoints. It’s vital to measure conversions per user with a weighted system that takes certain characteristics into account such as number of touchpoints, time elapsed between the start of the user’s search and the act of purchasing, and other metrics as well. I recall working on a project involving the sale of tyres and car-related products, where we analysed the most-viewed categories of accessories as well as products most often purchased together. Ultimately, our recommendation was to improve the customer journey by funnelling all customers through a step where related products were suggested. As a result, conversion rate improved and the average cart value markedly increased.
My recommendation to online merchants is to provide reassuring elements all along the customer journey through the product catalogue and purchase funnel, as well as clear filters for the user. And use technology that does not limit your possibilities (in an ideal world!). For example, product pages in a list should instantly display all the characteristics (colours, sizes, availability…).
E-commerce market manager at AT Internet
Find the right balance between acquisition budget and product margin
I see 3 main challenges for e-retailers in 2018. The first is, without doubt, the strong competition in this sector, which presents a challenge from both ends: On one hand, giants like Amazon and Cdiscount in France are well-known to the general public, with powerful marketing that just can’t be equalled. On the other hand, you’ve got competitors who are smaller, but there are so many of them. It has never been easier to create an e-commerce site in a few clicks, as CMS like PrestaShop, Magento, WiziShop, etc. greatly facilitate the process. Google dependence is also a reality. Whether it’s for SEO or for AdWords, having only limited visibility with Google is catastrophic for an e-retailer. Acquisition budgets are constantly being increased, and a lack of adaptability is an exacerbating risk factor. So, managing to attract a customer for the first time is already a great accomplishment. Creating loyalty with this customer to turn him/her into a regular buyer is an equally complex task.
After several years in the digital analytics field, I’ve seen e-retailer maturity really evolve. Ten years ago, data was “simply” used to create consolidated reports (lists of orders, lists of purchased products). Today, brands are hungry for recommendations regarding their analyses, suggestions for improving their product catalogues, etc. Data analysis is at the heart of e-retailers’ activities. Not only does data analysis make it possible to measure orders and turnover, but it provides an extremely detailed view of customer interactions with products. Data analysis also allows e-retailers to answer simple questions: Which products are most searched for? The most purchased? On which promo banners do visitors click? How often do they add products to their carts? How often do they add related products to carts? Etc.
This data is even more useful when we consider how diverse the challenges can be. For example, the purchase cycle is different whether it’s a car or groceries. While a car buyer might take several weeks to finalise the purchase (time to compare, to be sure about the purchase), a supermarket customer comes to buy groceries quite often Studying visitor behaviour enables e-retailers to adjust which products are pushed, and to therefore optimise adds-to-cart and final purchase. The ultimate objective is to find the right balance between your acquisition budget and product margin so that profitability is up to par.
Interested in analytics for e-commerce? Get more best practices and advice in our series of articles dedicated to e-commerce and download our free guide: