Utilizing Online Insights for Better In-Store Customer Experience

By Kevin Minkus

April 5, 2018

Here at Monetate Labs we work on problems on the cutting edge of ecommerce personalization. Recently our focus has been on omnichannel personalization. We’re interested in finding ways to help our clients drive better engagement and optimize customer experience across all their channels. A vital question in omnichannel is “how can we leverage data from one channel to enhance a customer’s experience in another?” Eliminating the data silos that exist between channels unlocks powerful opportunities to provide greater personalization.

According to an article in RetailDive, 67% of consumers research purchases online before buying in store. This means marketers have a great deal of useful data to help better engage their customers both online and in a physical store.

In fact, the recent Monetate EQ4 2017 data shows that 50% of all multi-device journeys last at least six sessions and 14 days. That is a gold-mine of data to help drive consistent, personalized experiences across all channels for a positive customer experience. So how, specifically, can marketers use website visit data to optimize in-store purchases? We conducted a case study with one of our clients to find out.

Examine purchase data across devices

As discussed, there are big opportunities for retailers to use online data to optimize in-store engagement. In fact, in our case study, customers who had previously shopped online and then purchased in-store were four times more likely to do it again.

The web conversion rates on those individuals will look poor, but if a retailer can understand it as an omnichannel pattern, they can better measure the impact of their web messaging. Web messaging should also reflect a knowledge of those patterns. Giving one of those individuals an online only promotion will be pretty fruitless and miss the mark.


Additionally, customers who shop in-store more frequently are more likely to follow up their web browsing with an in-store purchase. In fact, those shoppers were seven times more likely to do so according to our research. This is good news for marketers — it suggests there are many opportunities to leverage customer data to improve the experience of loyal customers and drive more revenue, regardless of channel.

Personalize web messaging

Data should flow in both directions to optimize customer engagement. If a retailer is aiming to drive a customer to an in-store purchase, the above point also suggests that less frequent in-store shoppers need a bigger nudge to entice them. A successful campaign designed to do this will target customers based on their in-store shopping habits, and not just their web habits, offering a holistic view of the customer.

Optimize in-store experience

How can marketers utilize online data for a better in-store experience? It’s about continuity of experience. If a web customer browsed a large number of similar products before coming into a store, a store associate can provide tailored product recommendations based on their online preferences. If a web customer only browsed a few products, an associate could have those products in the right sizes ready to try on.

Understanding and anticipating the needs of customers for better engagement is what retailers strive for. Delivering omnichannel personalization helps retailers achieve this. Customer data can be used to improve online experiences, but it should not be limited to that. Your shoppers are omnichannel; we need to start using online data to help personalize the offline buying experience too.

Kevin Minkus is a data scientist within Monetate Labs, where he uses math to develop ecommerce solutions both short-term and for the future to help solve diverse customer challenges. He enjoys working on problems that combine novel math with deep product understanding.

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