Personalizing Retail Customer Experiences: What’s the Missing Link?

The results are in, and the verdict is emphatic: Personalization works. And yet, though proven to drive revenue and customer loyalty to the point that one 2022 study found 86% of consumers appreciate personalized offers, many smaller retail businesses aren’t doing personalization as effectively as their industry-dominating counterparts.

It’s an anomaly that makes little sense. Even single-store, independent retailers possess large quantities of data, from customer transactions, browsing history, channel preferences, and mobile app usage to customer demographics. With such an abundance of data, any retail business should be able to deliver personalized messages to the right shoppers at the right time over the right channel.

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That’s the theory, anyway. Reality often has different ideas. In the case of retailers, the reality facing many is customer data that’s fragmented, inconsistent, and scattered across silos. The result is a lack of a unified, 360-degree view of data across all channels that’s so crucial for effective personalization.

Why Personalization Delivers Mixed Results

In the ongoing pursuit of personalization, retailers have tried various approaches.

One is for the IT team to stitch customer data together into a cohesive foundation. A complex endeavor, it is one that’s also labor-intensive, costly, and routinely drags on for many months where IT teams must hand-code integrations to connect applications and data.

Another tedious and resource-draining approach is for business-side staff to round up data into spreadsheets or databases. Yes, data can be fed into any number of personalization solutions, but if that data isn’t sound to start with, retailers invite the risk of off-target messaging that can damage brand equity.

To complicate matters even further, personalization projects are often isolated to a specific business unit, such as loyalty or marketing. Unless data is connected across all business units and to the full omni-channel environment customers use, from search to purchase to support, personalization results are going to be mixed at best.

Then there’s the fact that business applications change frequently. Indeed, it’s not uncommon for sizable retailers to have dozens of systems in place for e-commerce, point of sale (POS), loyalty, customer service, and merchandising, to name but a few. Whenever a retailer subsequently adopts a newer, improved system, whatever brittle integrations had been cobbled together previously must be rebuilt.

In fact, integration is the #1 obstacle that retailers face when implementing a new system, according to TotalRetail’s annual retail technology report for 2022.

The Ideal of Omni-channel Personalization

The increasingly sophisticated Integration Platform as a Service (iPaaS) market is emerging as a formidable panacea for these personalization challenges.

Leading iPaaS solutions are equipping retailers with intelligent connectivity and automation to break down stubborn data silos, accelerate business processes, and unlock the power of data — all critical elements for the most compelling personalization success stories.

For example, modern, rapidly deployed turnkey solutions designed to accelerate personalization allow retailers to personalize their customer journeys with a framework for data that is comprehensive, consistent, and timely.

Comprehensive. Retailers can achieve the ideal of omni-channel personalization by capturing customer interaction data from all touchpoints — not just a handful that may be necessary or specific to a function like eCommerce or physical stores.

Consistent. Data stored in disparate applications will always be inconsistent, with customer addresses and even names changing over time. High-order iPaaS data capabilities allow retailers to aggregate, cleanse, and enrich siloed data into uniform records that provide a single source of truth.

Timely. Personalization’s payback skyrockets when a retailer can do “marketing in the moment,” tempting customers with offers as they evaluate their options and close in on purchase decisions. Leading iPaaS solutions can feed near real-time activity data into personalization tools, triggering immediate outreach through email, digital ads, or text. The result is improved engagement, revenue, and customer loyalty.

The importance of a data-centric culture

As effective as iPaaS solutions are for driving personalization, their potential is hobbled where the retailer in question has not steeped the culture of their business in all things data.

With competition intensifying across the market, retail companies require deep insights into their data, which cannot be achieved by relying on either intuition or off-the-shelf software packages.

However, the adoption of a data-centric culture is not without challenges. Aside from legacy systems that are not compatible with advanced data analytics tools, there is typically some resistance from employees to change.

Here, plans for providing relevant workforce training becomes imperative. If expertise is lacking, companies can look to external partners who specialize in data analytics and the implementation of data-centric cultures.

Alternatively, retailers can look at their recruitment. Hiring data specialists can help improve the understanding of customer behavior and preferences, as well as identify the trends and patterns that lead to more informed decision-making. With data specialists on board, product offerings and marketing strategies can be more effectively tailored to meet the demands of customers.

Ultimately, it is this which leads to increased profitability and the prospect of growth.

Rethinking Retail’s Innovation Priorities

The retail industry has always maintained a strong focus on innovation. However, priorities have all too often centered around the latest and greatest front-end customer experience applications. Regrettably, this has come at the expense of back-end systems like integration platforms when the time comes for the C-suite to approve technology investments.

It’s a curious trend because the effectiveness of front-end applications depends heavily on their integration with other systems across the entire retail environment. Where these other systems are neglected, even the most impressive front-end applications have their potential muzzled.

Moreover, retail culture has often strayed from a focus on data with many viewing it as a less important than established cultures built around customer expectations of their product offerings. But, as we have come to learn, customer expectations are constantly evolving, and it is increasingly falling to departmental leads to make a business case for the tools that unlock the value of data for deeper personalization and for the people skilled in their usage.

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