Though brick-and-mortar continues to be the dominant channel in retail, consumers are becoming more channel-agnostic in the way they shop. E-commerce has long been a growing avenue for retail with a global market share that is expected to balloon to $5.5 trillion this year, an increase of almost 18% over the last two years; according to a 2022 report by Forbes, e-commerce sales grew 50% to $870 billion during the pandemic.
The shopping experience is in a constant omnichannel flux, where brick-and-mortar experiences remain central yet digital storefronts and experiences are now similarly crucial. With physical stores adopting new technologies such as digital signage and AR/VR to bring online shopping features into real world retail, the offline and online worlds are merging and the boundaries that once defined channels are now blurring.
Progressive retailers are seizing a ‘channel-less’ model with customer data at its core – powering experiences and commerce across every touchpoint.
It has never been more vital for retailers to leverage that customer data and build profiles to create personalized experiences that meet demands with unprecedented precision, robustness and efficiency. Putting it plainly, for anyone who didn’t already know, the long-forecasted future of data-driven retail is now fully a reality.
Poor Data Processes: A Barrier to Success
During a digital transformation program, many retailers have the right intentions when it comes to how they want to leverage their customer data. For example, to improve experiences, to encourage loyalty, to provide the perfect product recommendation.
The problem is often that they don’t first consider whether they are capturing the most relevant and accurate customer data.
“When we begin work with many of our retail (and other) clients, we often find they lack a strategy to monetize their data. They tend to have data on the same customer profiles duplicated and spread across multiple disconnected platforms,” notes David Andersen, North America Insight & Analytics Advisory Lead for Avanade, a leading digital innovation partner that helps organizations across the globe to accelerate their transformation through privileged access to the Microsoft ecosystem.
Counting the Cost of Disparate Data
Poor quality data leads to incomplete or inaccurate customer profiles. The knock-on impact of this carries wide-ranging implications that many retailers may not immediately realize.
Primarily, organizations operating from poor quality customer profiles are losing out on revenue. These profiles generate inefficiencies that can result in disappointing outcomes such as marketing campaigns that are misaligned with target customers’ needs and wants.
Caleb Benningfield, Principal Solution Architect, for Amperity, a customer data platform that helps companies put data to work to improve marketing performance, build long-term customer loyalty and drive revenue.provides a specific example to underscore this point.
“The average duplication rate for a well managed customer data set is about 7%. This means that 7% of customers have more than one record assigned to them. So if a company spends $10 million per year sending out customer emails to a targeted list, this might mean that up to $700,000 of that investment is wasted, sending two emails when only one is required. Add to that the frustration caused to customers, and that’s quite the waste of your marketing budget.”
Benningfield continues, “The most profitable customers often produce the most data for a business. By not identifying them correctly, brands miss out on some of the biggest revenue opportunities. More worryingly, the poor experiences brands provide because of duplication may actually cause customers to churn in the future.”
Ultimately, incorrect beliefs about your customers and their preferences creates a myriad of systemic issues that can cause a domino effect – resulting not only in constrained sales returns, but also in misaligned broader strategic initiatives and programs.
First-Party Data to the Rescue
First-party data collection can help retailers to build empathy and customer loyalty, by improving data accuracy. But doing that requires retailers to overcome their customer data strategy hurdles. That’s where the unique partnership between Amperity and Avanade comes in.
For example, Amperity has been of paramount importance to accelerating analytics at Deckers Brands. Moreover and most critically, Amperity allowed Deckers to “have confidence in [our] customer identity resolution, [which] is really the bedrock to any consumer analysis. With Amperity, we’re able to dissect how customers are stitched together at a very granular level, so if there is ever any question as to how a customer ID is generated, we’re able to speak to that with certainty.”
Avanade, meanwhile, has helped clients to accelerate performance by leveraging data collection, analytics, and new AI implementations.
When a global food retailer was looking to improve store accuracy via new financial forecasting techniques, Avanade was able to step in and implement predictive models that resulted in a 7.7% improvement in accuracy for store forecasts along with a 19% improvement in accuracy for category forecasts.
Now, Amperity and Avanade’s partnership is helping leading brands to shed their reliance on third-party cookies and implement sustainable first-party data solutions.
And clearly this matters today. Retailers seeking to capitalize on customer data are keenly aware that third-party cookies are dying and will be completely gone by 2024.
Indeed, later this year, numerous customer privacy regulations such as the California Consumer Privacy Act will begin requiring users’ explicit permission to share and use data generated from online activity.
By leveraging first-party data, retailers stand to win in a number of key areas.
First and perhaps least surprisingly, having a first-party data collection and management infrastructure cuts out the need for third-party data management services altogether, resulting in a significant shorter-term cost savings.
The second benefit is directly related: despite what third-party providers might lead decision-makers to believe, third-party data can contain significant inaccuracies, particularly when it comes to identity resolution (matching data with the right customer profiles).
“Match rates fall to 60% or lower. A strong foundation of unified customer profiles made from accurate first-party data drives stronger results, with match rates that can reach over 80%,” argues Amperity.
Lastly, because you can trust and rely on the data you’ve collected as a first party, you’ll get to know your customers better than ever before. That means more personalized marketing, improved customer experiences, increased sales and loyalty.
Be Wary of First-Party Data Pitfalls
While there are myriad benefits to first-party data management, there also needs to be a keen awareness of what could go wrong.
Without a commitment to maintaining and validating data accuracy, your first-party data transformation is likely to fail. Managing your data properly is critically important to prevent false impressions or inaccurate conclusions.
The Danger of Misidentifying your Best Customers article by Amperity states “Most customer data management and unification practices cannot deliver an accurate view of their customers. Identity resolution, the act of merging consumer data with its matching profile, is hugely important — if that isn’t done properly, then the marketing steps that follow are guaranteed to be less effective.
Even properly collected and formatted data is useless if grouped incorrectly, as the right data merged into the wrong profile is still going to be inaccurate.”
Then—while the overall cost compared to using a third-party data platform should be lower—there’s an initial expenditure you’ll need to build a business case for. Investment in ongoing training is another oft-overlooked consideration.
Finally, as with any transformation, change doesn’t happen simply by switching off one platform and moving to another; as Avanade’s North America Retail Lead Greg Jones highlights. “We repeatedly see retailers’ efforts to monetize their data fail because they underestimate, or ignore, the scale of change management programs that are required.”
Retail data strategies cannot be successful unless core processes are communicated to the entire organization. All employees must know their part in the strategy in the data-chain. It is important to take the time to implement that change management strategy and set up training ahead of time so they can hit the ground running.
In brief, by choosing the right partner and spending time to develop a strong first-party data collection and management strategy, retailers can maximize the value of their customer data—in a way that’s efficient, scalable and sustainable.