What NOT to do with your eCommerce customer data
It’s no secret that we love data here at Retention Science. And for good reason: demographic, social, transactional, and behavioral data provide deep customer insights for marketing campaigns, product improvements, and how to better serve the customer.
As essential as it is for eCommerce businesses to focus on collecting clean, usable data from their customers, it’s even more important to find and use this data correctly. When incorrectly implemented, data-centric strategies can end up hurting rather than helping.
When dealing with customer data, here are some common missteps to avoid:
Giving customers the silent treatment
Technological advancements in behavioral targeting and analytics now enable you to collect data and activity without ever having to communicate directly with shoppers. Rather than relying on the past method of asking customers to fill out interest profiles to figure out what products to recommend, now you can just track their browsing history on your site.
While there are obvious benefits to passive data collection – fast, convenient, and hugely informative – doing it too much can and will distance shoppers.
Collaboration and communication with your customers is still key. Effective engagement with your customers means using the collected data to enhance your communication, not replacing it completely.
Interact with your customers. Incorporate humor or clever graphics in your quizzes and surveys to encourage responses. Assist shoppers while on your site, and provide ways they can send you feedback. Don’t underestimate the effectiveness of simply asking for more information – just emphasize that it’s so you can create a smoother and more satisfying experience for them.
Letting shoppers in on your data-gathering efforts can strengthen your relationship with them by showing them you care. And from a data standpoint, actual communication or survey results will supplement the information you already have, enabling a more complete view.
Bombarding your customer
In the same vein, it’s easy to get carried away when trying to incorporate the data you have into personalization strategies. One of the most common tactics for many eCommerce merchants is remarketing, which shows customers related ads when they navigate away from your site without purchasing. The theory is that remarketing will encourage your customers to come back – but if you’re not careful, it can have the opposite effect.
For example, I was browsing sandals at an online retailer recently, and ended up leaving the site without purchasing anything. Within a few minutes, my browser was inundated with remarketing ads – and not just one, but repeats, shown side-by-side. Just a few hours later, I’d received reminder emails with the exact same products.
Three sandal remarketing ads next to each other on my browser
It was too heavy-handed for me, and it ended up turning me off instead of converting me into a customer. Don’t get me wrong – I’m a big advocate of tailored marketing messaging – but a blitzkrieg of remarketing ads is not so much personalization as it is sensory overload. Remember: there is such a thing as overkill.
To avoid this, set a frequency cap on your remarketing ads so they don’t appear everywhere. Also, make sure you’ve gathered enough data about your visitors to determine the right messages and channels to market on. Don’t emphasize every platform or channel. Instead, figure out the most effective way to reach each consumer. Are Facebook ads the best way to go, for example, or should you send an email? Should you serve up mobile ads? Make sure you have sufficient data to answer these questions before launching your campaigns.
Only focusing on one data point
Speaking of collecting sufficient data, not comparing information you collect from one data point to other data streams can lead to incomplete or incorrect insights. You may assume you know what your visitors are thinking based on browsing history alone, but social media data, email open rates, and transactional history could be offering a different view.
If the online shoe retailer from above had analyzed my email behavior together with my browsing and purchasing history, they might have been able to gain more insight on the best time and way to remind me about those shoes. Instead of turning me away, a well-timed coupon or free-shipping offer might have been the final step in getting me to convert.
It’s important that you examine and correlate information across multiple sources so you can determine the most effective courses of action. Every customer is unique, and the best campaigns are ones that are tailored to that fact. Gathering enough data from varied sources will allow you to understand your customer better, and using that data wisely is what will help get that sale.
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ReSci is a team of marketers and data scientists on a mission to democratize AI. We make powerful recommendations and predictions accessible to brands. Find out how we can help you connect with your customers.