Since the landmark year of 2020 ended, you’ve probably read somewhere that the e-commerce sector boomed during the coronavirus crisis, seeing ten years worth of growth within just a few months. No one needed an article to tell them this: we’ve all experienced how the convenience of e-commerce enabled us to continue shopping and ordering groceries or prepared meals during a time when we weren’t allowed to leave our homes.
What most of us haven’t considered is how this has changed digital marketing in the e-commerce sector. A recent insights article from McKinsey argues that the marketing world that’s still to come (“the next normal”) is predicated on data-driven insight and a revolutionizing of outdated e-commerce data modeling. The past year should have yielded a gold mine of customer data and market understanding, but has for the most part been a missed opportunity because data collection and analytics was never robust or sophisticated enough to dive into the kind of granularity that’s now possible. And as the customer base shifts with increasing numbers of digital shopping options, customer retention will rely — more than ever before — on unified customer data captured in real time to enable precision marketing.
We believe that we are already in the new normal, not waiting for the “next” normal, even if the new normal includes an adjustment period during which businesses of all sizes attempt to recalibrate for changing customer behavior.
A new e-commerce paradigm: Don’t buy into old data models
What retailers thought they understood about their customers has turned upside-down during the pandemic. A pandemic will do that, as consumer psychology shifts from a mindset of nice-to-have to must-have though digital shopping. Because old data models, and a predictable, if slow, adoption of e-commerce made consumer behaviors, habits and tastes hew to the expected. Some changes could have been foreseen with better risk-predictive thinking. For example, the online travel and hospitality sector, and their offline counterparts and service providers, have been hit hard, as no one has been able to travel. Many retention-marketing programs have been hit as well because the digital arm of these kinds of businesses rely on continued patronage, loyalty program engagement, and are arguably miles ahead of traditional e-commerce business in tapping into the customer data they have at their disposal.
The acceleration of e-shopping behavior has ushered in a new e-commerce paradigm, but retailers were unprepared for the change, which isn’t surprising because who is ever prepared for the business downturn of a natural disaster or global health crisis?
But where the massive acceleration of e-commerce adoption should have buoyed e-commerce retailers and sent retail marketers into action to sustain and retain their customer base, they have dropped the ball. For the most part, e-commerce companies have been remarkably slow to respond to the need for new data models, opportunity predictors, and accuracy and timely insight into their existing customers. This isn’t to say that retailers haven’t been busy with other, more immediate concerns, like supply-chain and logistics issues and in many cases becoming digital retailers for the first time.
This is more a cautionary warning: if you’ve fallen behind and need to reshape your data strategy, or need to develop a ground-up understanding of your customers, there’s no time like the present. The exponential growth in e-commerce adoption isn’t likely to reverse itself.
Assembling the precision marketing puzzle pieces for e-commerce
What are some of the key pieces of the precision marketing puzzle for e-commerce?
- New data: Tap into new data sources to prevent churn, personalize and tailor messaging, make bespoke offers, etc. This might extend your current data sourcing to move from just in-house customer data to include third-party analytics, location-based/IP-based/device-based data, social media data, competitor data, and so on.
- New data models: Be sure to update your data models along with sourcing new data. Just adding new data into your tools without applying the right, or new, data modeling techniques, won’t give you a complete picture and won’t get you much further than where you already are.
- New scale: Taking data analytics to the next level requires some investment in technology (both the tech itself and the education and cultural change it takes to scale up internally). With this new scale, it becomes easier to approach precision marketing, retention and growth with agility and speed, and shift gears as needed. This will mean, at some level, machine learning and AI, but it won’t have to start that way. It’s what’s coming in terms of scalability.
- New approach: Upgrade your insight, upgrade your marketing. Focusing on precision marketing as part of the mix ensures that you retain and understand existing customers and their changing needs, thereby increasing ROI and loyalty.
What does your digital marketing for retention look like?
The new e-commerce paradigm demands revisions to existing digital marketing and data analytics strategies. Understanding customers, both new and old, requires the right kinds of accurate and fresh data, applied to retention activities. Do you know what is most relevant to your customers in a changing landscape, whether it’s defined by a stay-at-home mandate, a global pandemic, or simply by becoming an e-commerce convert? We can help you answer these questions and respond to the transformative growth opportunities available during even the most uncertain times.
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