The COVID-19 pandemic has made customers hyperaware of physical touch points while shopping, so it comes as no surprise that retailers across verticals have seen substantially more customers opting to use their digital commerce experience (DCXs).
For many c-stores offering a digital experience today, their DCX consists of an online ordering interface, SMS or email marketing program, or mobile app featuring order ahead and/or a loyalty program.
This growth in usage has rewarded retailers with a swell of newly acquired and activated digital consumers; however, user retention rates have lagged behind other verticals, which means convenience and fuel retailers must now pivot to focus on more critical phases of the consumer lifecycle: engagement and retention.
Unlike most physical counterparts, DCXs provide retailers the opportunity to track intermediate user interactions. This provides data on consumer outcomes (registration, purchase, etc.) — which, if captured and analyzed properly, can provide the retailer with meaningful insights into what is positively and negatively influencing these outcomes.
Optimizing the consumer experience through DCXs is where the opportunity now lies for convenience and fuel retailers.
Gaining Behavioral Data
Before developing data models and insights, however, DCX optimization requires breadth and depth of consumer data. It is imperative that retailers first focus on the “oil” that makes the optimization engine possible: behavioral data.
While basic user demographic and identifier data is essential to facilitating DCX purchases and operating rewards programs, best-in-class retailers go well beyond these data sets and enrich their consumer profiles with triggers and associated behavioral data.
Examples of triggers include:
- Messages (push notification, SMS, email, etc.)
- Suggestive selling (i.e. after items placed in the user’s cart)
Proper tagging and event tracking within all DCXs (mobile apps, web apps, etc.) allow retailers to measure outcomes, for example:
- Install-to-register conversion rate and time
- Install-to-purchase conversion rate and time
- 30-, 60- and 90-day retention rates
- Message open and conversion rate, by communication channel (email, in-app, SMS, push)
By wrangling these types of data points and associating the data with outcomes (such as installed, registered, payment loaded, activated, super user, abandoned purchase, redeemed promo, etc.), best-in-class retailers structure their funnel analyses to not only determine conversion rates for each outcome, but also to identify points of friction that lead to sub-optimal conversion rates. For example:
- If the install-to-register rate is below industry average, how can friction at the point of data collection be reduced?
- If the install-to-purchase time is above industry average, what steps can be optimized and/or removed in the buying process?
- If the 90-day retention rate is below program targets, how can messaging and offers be tweaked to drive continued usage?
Retailers who prioritize behavioral data collection and optimization of the consumer experience in this way will thrive in the digital world and excel over competitors who churn new customers and retain few. And if the consumer trends driven by COVID-19 transition into permanent trends, consumers will continue to reward these DCX-focused retailers with their loyalties. CSD
Patrick Raycroft is the Convenience and Energy vertical lead at W. Capra Consulting Group, helping clients across retail and fuel identify and implement technology solutions that minimize risk exposure, enhance consumer experiences and improve operations. He can be reached at [email protected] or visit www.capraplus.com.