For retailers, relationship building is make or break. Personalization has become a commonly used strategy for connecting with shoppers, no matter what channel they’re using to shop. In fact, 76% of consumers become frustrated when an ecommerce site doesn’t use personalization. Beyond satisfying shoppers, retailers can use personalization to make sense of first-party data and to put it to good use.
But how do retailers know if they are taking advantage of all the opportunities within the umbrella term of “personalization”? How will retailers know if their personalization strategy is working?
Before we dive into how to evaluate personalization, let’s discuss how personalization should be implemented to maximize success down the road. Hint: It starts with email marketing and ends with continuous testing.
How does the personalization journey begin?
Personalization is a moving target because the customers are a moving target. For example, the shopper who bought yeast in bulk to keep up with the bread-making trend in 2020 might be back to purchasing premade loaves. Or they might be trying a new diet craze and avoiding bread altogether. The point is, shopper behavior changes rapidly. As a result, personalization involves constant experimentation because there are many variables for both new and returning customers. Influential factors include personal preference, time of year, changing demographics and circumstances and more.
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So when retailers first invest in personalization, their goals might look different than when they have a stronger grasp on their customer base. With that in mind, the first step is to gather customer data. This will include data on customer loyalty, inventory, transactions, pricing and customer engagement and behavior. This data may seem overwhelming at first, so some retailers choose to focus on their top customers, and begin by creating a customer profile for them using these disparate data points.
Which customer segments benefit the most from personalization?
For two of Birdzi’s retailer customers, let’s call them “Super Store” and “Savvy Shop,”, the most important shoppers were from one all-important category – the “omnishoppers.”
These customers make both in-store and online purchases, and they tend to be the most valuable, loyal, and engaged customers. A Harvard Business Review report found that omnishoppers, in comparison to those who only use one channel, spent 4% more on every shopping trip in-store and 10% more on every shopping trip online.
With so much more at stake, this group is a worthwhile target for retailers looking to begin their personalization journey. In fact, “Super Store’s” omnishoppers spent 85% more money than online-only shoppers and 140% more than in-store-only shoppers.
Similarly, omnishoppers visiting “Savvy Shop” spent 130% more than online-only and in-store-only shoppers. In both case studies, these customers also made more average trips per week with larger basket sizes consisting of more categories, making them the perfect target for personalization testing.
How should retailers test personalization?
A cost-effective way to test personalization is through email marketing. This is the simplest medium because online-only personalization via email marketing does not have any incremental costs associated.
Email personalization can also be tested in batches and used to make clearer correlations to results. Plus, customers have the option to opt in and opt out, so the test should not ostracize any customers, even if they are wary of data usage.
This low-cost option serves to benefit the potential skeptics on the retailer’s team. Yet if the retailer witnesses the results “Super Store” and “Savvy Shop” did, the ongoing investment into new personalization touch points will be an easy decision.
How can retailers evaluate personalization?
Retailers like “Super Store” and “Savvy Shop” must evaluate personalization as a real-time and ever-improving asset across customer-centric touch points. This evaluation must be based on deep customer insights pertaining to the shopper’s purchasing intent, shopping journeys and other KPIs.
For retailers just starting their personalization journey with email marketing, commonly used evaluation metrics include unique opens and click-through rates. But these alone don’t prove the value of personalization; only a lift in profits and other meaningful KPIs will do that.
Another point to consider: each retail sector has its own KPIs. For grocers, a boost in visit frequency, breadth of categories shopped and basket size are crucial indicators of success. In fact, grocery retailers have witnessed as much as 38.2% growth in the number of categories shopped, a 23.6% growth in the number of trips per shopper and a 16.6% growth in the spend per shopper from a single personalization campaign. With results like these, grocers can rest assured that they are moving the needle with personalization.
At the end of a personalization trial, retailers should review KPIs carefully and then ask themselves, “Are we moving shoppers up the chain of loyalty?” If these evaluations are favorable, it’s time to move forward in personalization implementations.
Once email marketing has been mastered among omnishoppers and KPIs have improved, it’s time to branch out into other areas of personalization. This can be through expanding the customer segments incorporated or reaching new digital touch points.
Where should retailers go from here?
Personalization is still a budding strategy for retailers, with new technologies emerging regularly including new mobile app options, location-based in-aisle recommendations, kiosk advances and more. The best part of personalization (besides the incremental lifts for KPIs!) is the natural feedback loop. As this technology becomes more mature, new opportunities will emerge that retailers will need to experiment with, evaluate and refine, ultimately improving their business every time. The future of personalization is the future of profitability.
Shekar Raman is CEO and Co-founder of Birdzi, a grocery retail AI solutions company that was inspired by an idea his 11-year-old daughter had about locating products in the supermarket. He is passionate about building data-driven technologies leveraging AI and machine learning to help retailers and brands elevate the customer experience.
