How big data fits in with eCommerce Customer Engagement

Retail / eCom   |   
Published April 23, 2019   |   

In the field of marketing, the term “engagement” is thrown around a lot. Just about every type of campaign will be aimed at boosting “engagement rates.” For instance, success in social media marketing is often measured by engagement indicators such as likes, shares, comments, and click-through-rates.
There is no doubt that building meaningful connections with your customers leads to profitable relationships that can help your business grow. But as technology becomes a more prevalent part of consumerism, it can actually breed a level of disconnect between customers and companies.
Technology has made it possible for businesses to reach larger markets than ever before. However, this often leads to companies treating customers like a figure in a database. According to a study conducted by Accenture, a digital disconnect has caused 52% of consumers to switch providers because they missed the human connection that was replaced with technology.
So, how exactly can businesses cultivate and nurture these connections in today’s highly digital age?
Surprisingly, the answer here is to integrate more technology, specifically big data systems. By using these tools to understand your customer’s behavior and create a better experience, your company can effectively engage with customers in a way that everyone wins!
Here’s how.

Customer data for customized product targeting

Personalization has a lot to do with the customer experience these days, considering the fact that consumers are highly receptive to customized offers and product recommendations. In the e-commerce sector, one online business idea that really took off is offering personalized on-demand custom products.
Take the company Care/Of as an example. They offer vitamin and supplement plans that are completely customized based on factors that are unique to the individual customer, such as their age, weight, fitness levels, goals, and specific health concerns.
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These types of products have high demand, but it is important that brands know how to market them successfully. By applying big data insights from your audience, you can create hyper-targeted ad campaigns for various niches that would be interested in specific products.
Care/Of did this by using their social media audience data to create buyer personas and identify specific markets that would respond to specific messages. From there, they used big data to determine the type of content that would work best with each segment and adjusted their messaging accordingly.

Optimized buyer’s journey mapping

Knowing when and how to re-engage a customer can do wonders to increase the number of conversions, plain and simple. This is often best done by incorporating the type of content that will have the biggest influence on your customer’s trust as well as their purchasing incentives.
Customers in the last stage of the buying process tend to be more interested in unbiased assessments and third-party reports because they want to get a full picture of the product.
The SaaS company Trustpilot understood that in order to grow the number of customers moving from the final consideration phase towards a purchase, they needed to increase their visibility on niche third-party sites, like Finances Online. This fulfills their customers’ need for fair-minded information that would help them make a more informed decision.
Big data can be useful here for automated targeting that brings the right content directly to the customer. Say that a customer visits your site, looks at some products and adds an item to their cart, but then leaves without a purchase. A well-placed ad or an email promoting brand pages on niche third-party sites could potentially turn them into a paying customer.
Obviously, this type of trigger-based strategy requires loads of behavioral data and smart automation systems. You will need to have a deep understanding of the sales funnel for your specific audience. Big data is the solution here because it provides online sellers with the information, they need to create a realistic customer journey map. From here, you can identify falling off points where customers need to be re-engaged through content, retargeted ads, or promotions.

Incentivized loyalty through personalized perks

Most businesses want to offer more personalization since it has such an incredibly strong influence over conversions. Proper data analysis is the only thing that makes this possible because personalization needs to be based on relevant customer information in order to be effective.
One of the best ways that online retailers can use this is to create customized incentives for each customer based on their product purchases and views. According to Bond Insight’s study, 87% of consumers stated that they would willingly share personal details and allow companies to track their behavior in exchange for personalized rewards or offers. Furthermore, this report found that businesses offering customized loyalty programs saw up to a 99% increase in customer spending.
Obviously, good data and proper execution is the key to making a customized loyalty program work. Starbucks does a great job of this through their rewards programs. The data-fueled program sends out specialized offers that are based on the customer’s favorite purchases. From here, Starbucks subtly encourages higher buying volumes as an incentive towards a free reward.
Clearly, Starbuck’s approach is based on the immense amounts of behavioral data that they have access to. Now, this may not be possible for a smaller e-commerce organization to do, but there are ways that Big data can still be useful.
For example, simply analyzing how often customers tend to purchase items and identifying typical purchase patterns (like frequently bundled products) can be used to create custom incentives. If a customer purchased an item two weeks ago and are likely to run out, they could be reminded to repurchase, along with a custom discount and recommendations for related items.


Engaging with your e-commerce audience is incredibly important – and not just for the initial sale. When customers feel connected to a brand, they are more likely to be loyal and recommend it to others. Be sure that you are doing all that you can to create this connection by utilizing big data in a way that cultivates meaningful engagement.