During a recent conversation I had with a retailer about personalization’s role in customer loyalty, he told me that he considered it a key differentiator in providing a positive experience. While I don’t dispute the value of personalization, I kept prodding deeper. What is motivating consumers to want a more personalized experience with a brand? Is it just a matter of delivering a relevant product or is there more to it?
The reality is, creating a personalized experience means much more than just delivering the right product at the right time, or providing shoppers with a recommendation based on a previous purchase. To truly personalize the retail experience, you must understand shoppers’ motivations for why they interact with your brand. And that means getting a hard grasp on data.
By harnessing data from multiple touch points throughout the customer journey, retailers can better understand the vast and varied motivations behind their customers’ purchase decisions, and ultimately create deeper brand affinity. Here’s a closer look at how they can do this:
Multiple audiences, multiple motivations
What motivates one shopper to place an item in a cart isn’t necessarily the same for the next shopper. However, there are a few key factors that consistently sway shoppers’ purchase decisions: time savings, price, brand loyalty and the products themselves.
Understanding these different motivators can help retailers personalize much more effectively. This includes how they merchandise product online and in-store, invest in training for staff and, of course, determine pricing and promotional strategies.
For example, let’s say you have a customer who is motivated by time-savings. He or she may not purchase a heavily discounted product if it means the hassle of driving, parking and finding the product in the store. But that customer may purchase a product at full price online if you offer free shipping and deliver the promotion straight to their Instagram feed.
In another instance, a customer who is motivated by brand loyalty may be more inclined to make a purchase if they are invited to a VIP customer event. Retailers such as Sephora have leveraged events to create a sense of exclusivity among top shoppers and cultivate a stronger sense of affinity for the brand.
In both these situations, personalization is taken to the next level and data is used to craft experiences that appeal to specific customers and not macro-segmented targets.
Data is the key to making personalized experiences return value
So how can retailers successfully make their data work for them? In the recent report from Deloitte and Salesforce entitled “Consumer Experience in the Retail Renaissance,” we found the majority of retailers (nearly 60 percent) are struggling to improve the customer experience at the top of the funnel, where discovery and brand awareness occur.
Indirect data sources are increasingly important to building complete shopper profiles and informing a holistic customer journey. However, 65 percent of branded manufacturers can access only a moderate amount of consumer data via indirect channels. Or none at all. This is a huge barrier to their success. Those brand leaders that can harness data are seeing an impact on the bottom line; they report a revenue increase of at least 10 percent.
Another data source retailers can tap into lies within the retail organization itself. When brands break down internal business siloes and integrate functions such as customer service, marketing and sales, they can construct a more complete picture of a shopper’s motivations and tailor conversations that drive more productive brand interactions. For example, say a number of customers report an issue with a product to customer service. If that data is available throughout the business, other departments, such as marketing, can use it proactively to check in with customers, circumvent issues and offer tailored promotions to remedy any negative brand sentiment.
This kind of data is also essential to using technology more effectively. AI and machine learning is this year’s hot retail topic for tailoring pricing and promotions in real-time or providing relevant product recommendations to customers. But by leveraging customer data and breaking down siloes within businesses, AI can also be applied to a wider array of tasks such as script generation for marketing campaigns or customer service.
New understanding of personalization
To return to my conversation with the retailer, personalization is clearly important to create a positive experience, but it is also much more. Personalization is about recognizing individual shoppers’ motivations and acting on them so brands can engage in rich and contextual conversations with consumers.
Personalization is not a new concept. Tailoring it to consumer motivation is key and requires rich data insights. How frequently someone shops, how much time they spend in store, what they purchase, the route they take to purchase—not to mention what they purchase elsewhere, gleaned through third-party insights—all help retailers better understand individual shoppers. Using this data as a bedrock, retailers can craft more effective strategies for attracting and converting shoppers, and introduce technologies to streamline the shopping experience. This will shift the top of the funnel from an area for improvement into a competitive advantage.
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Kevin Hogan is a senior leader in Deloitte’s Retail and Commerce Practice and consumer engagement leader at Deloitte Digital. He specializes in helping companies transform their business to take advantage of emerging digital opportunities designed to drive revenue growth, increase cost efficiency, and optimize the customer experience.
