Part 3 of 5: Technology as the great enabler
I’ve been saying throughout this series that e-commerce is no longer an option. This means that as retailers we have to invest in technologies that deploy and support an e-commerce offering, including all of the interactions with the shopper through to order tracking, fulfillment, supply chain, and inventory planning. But allowing shoppers to simply buy online is not enough.
Today’s shoppers are conditioned (mainly by Amazon) to expect instantaneous cross-sell and upsell offers, personalized to their preferences. And this level of personalization is absolutely possible for the rest of us: with a customer engagement intelligence platform, any retailer can achieve this next-level performance.
With millions of customers, the idea of analyzing each of their item-level purchases and all of their interactions with our brands seems an incredibly daunting task. But a customer engagement intelligence platform lets us do that and more, maximizing the value of our digital engagement with shoppers. It can determine if an individual customer prefers private brands over national brands; whether they buy items on promotion or at the everyday price; whether they prefer healthy or “free-from” items; if they prefer premium items or opening-price-point items; what brands/items they have loyalty or affinity for; what stage of life they’re at; whether they prefer to cook or are time-starved... the possibilities go on and on.
The right platform will pre-calculate the likelihood that each customer will respond to an offer on all products a retailer offers and their product affinities for all items. This is the secret sauce to making personalization work. To take things a step further, the platform should also pre-calculate factors like the customer’s item price elasticity, allowing us to offer personalized prices that will maximize the chances a customer will buy each item and maximize the ROI.
Identifying individual customers
To make the customer engagement intelligence platform work, each customer must have a unique identifier in the system. We can identify customers in a few different ways, the easiest and most comprehensive of which is a loyalty program. We can even start to get insights through an e-commerce site or app that gives each shopper a specific identifier. Once each customer is identified, we can then match transactions to the individual or household, and that information allows us to deliver truly personalized benefits.
Of course having the data is only the first step. Once we’ve got a customer engagement intelligence platform running and individual customers identified, we have to use the information to change how we work all across our businesses, including marketing, merchandizing, and along the value chain to manufacturing. Customer marketing, for example, can now be made relevant to each individual customer while also being timely, and response rates can be high while also delivering incremental sales that lead to even higher ROI. And we can do all of this on a consistent and repeatable basis, just like Amazon’s recommendations.
Of course, this means we must invest in expanding our offer banks. It’s not uncommon for a retailer’s current systems to only accommodate a few hundred offers, which seriously limits the capacity to deliver personalized offers. So we need to invest in technologies that allow for dramatically expanded offer banks, so we can derive maximum value from our new capabilities.
All of these solutions are already available and in use today, so technology should not be one of the main challenges preventing progress. Don’t have technology expertise within your organization? Consider partnering with external parties that have very specific expertise in areas like advanced analytics – so you can remain focused on your core business of serving your customers.
This transformation doesn’t end with technology, however. Technology is only a piece of the puzzle. In my next post, I’ll talk about how we need to transform our businesses – our organizational structures and our processes – to really make this work.
When investigating technology options and their impact on the business, we need to consider multiple factors, including:
- What data do we need to capture?
- How will that data be captured/stored?
- How will that data be assimilated/cleaned/aligned?
- How will the data be analyzed?
- How will the analyzed data be used across the business to enable decision-making?
- How will the data/insights/actions be distributed and presented to decision-makers?
- How will decisions be tracked?
- How will decisions be measured?
- How will we continually learn?