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Three Common Mistakes in Retail Personalization

When purchasing gifts for someone we care about, we always strive to find the perfect thing that combines their passions – for instance, both wine and baseball. This level of personalization is incredibly difficult, requiring deep knowledge of a person’s likes and dislikes. Yet this is what retailers are faced with doing every day. Given the level of insight that genuine personalization requires, it’s no surprise that retailers often fail to establish the sticky relationships with customers that they need to in order to stay competitive.

The problem is not that retailers don’t know about the power of personalization – 96% of retailers acknowledge that it influences what consumers purchase in some way,[i] and close to the same number say that personalization is a strategic focus for them.[ii] Yet customers are not feeling the love – one-third of consumers wish their shopping experience was more personalized than it is.[iii] So where does the disconnect between strategy and execution come from?

Simply put, implementing a personalization program and getting it right is difficult. For instance, it can be easy to mistake segmentation for personalization. These days, tailoring offers and services based on a customer’s age bracket and other demographic information isn’t enough. As another example, retailers can easily go overboard by contacting their customers too frequently or in the wrong way. If you blast content to a customer every day with the same offerings, you risk driving them away.

When trying to execute on retail personalization goals, there are three common mistakes that many retailers make:

  • They don’t act on all of their data
  • They don’t ever reevaluate their marketing approach
  • They don’t take full advantage of the technology available to them

Below we will explore these mistakes and what strategies retailers can employ to avoid them.

Mistake 1: Retailers don’t act on all of their data

The first error many retailers make is that they capture and act on basic demographic data but don’t combine it with other potential data sets. The problem is not that retailers don’t have or can’t get data from customers – in fact, people want to engage and will share their data with retailers if it will improve their experience. Nearly half of consumers say they are receptive to having trusted brands track their data in return for personalization.[iv]

The most sophisticated retailers are able to layer all of the data they receive, combine it with other sources, and use analytics to predict behavior or provide personalized offers. These advanced analytics can mean extra work up front, but can bring huge rewards. Layering data from weather, trend forecasts, and multiple sales channels can let you target customers effectively – in some cases boosting purchase frequencies by 18% and resulting in a 25% larger average check. For instance, retailers can tell that this year they should recommend polarized sunglasses frames to a customer as soon as temperatures rise in the spring, since the customer purchases a set of frames just about every June.

Another key is to use analytics insights to help customers discover new products inspired by their unique history and preferences. It’s not useful to recommend what customers already buy – retailers see the biggest returns by encouraging customers to change their behavior and try new things.

And these recommendations are what customers want – 92% of consumers surveyed by Infosys look to discover new products[v] and half of them are more likely to return to and purchase from a website that makes recommendations.[vi] By directing them to products that they are interested in, customers see that retailers care about their time and are listening to their preferences. With personalized recommendations, you are giving them “guided serendipity”[vii] in their shopping experience. Clearly, simple if-then rules for offer personalization are not enough – customers expect sophisticated experiences that change with their needs and that are refined every time they shop.

Mistake 2: Retailers don’t reevaluate their marketing approach

Even if retailers build offers around sophisticated data analysis, many set up rules and logic at the beginning of their process and assume they can leave them. Personalization is not a set-and-forget process – customers’ desires are constantly changing, and retailers need to keep up.

However, this is a difficult task. Only 12% of retail executives in a Microsoft survey said that their companies are extremely effective at using analytics to personalize promotions for specific customers.[viii] It’s key to remember that rules are a good start, but your strategy needs to be built on more than that. One solution is to constantly evaluate and adjust ads, content, and data collection methods, testing frequently with A/B platforms to see where small changes can lead to big returns.

Personalization returns carry far past shopping carts and order confirmations into email outreach, offers, and incentives, enabled by customer data. By constantly reconsidering their personalization strategy, retailers can reach their customers in a unique way. The ultimate way to differentiate is to embrace new technologies that can provide a dynamic shopping experience upon click-through.

Mistake 3: Retailers don’t take full advantage of the technology available to them

Implementing the latest technologies is one of the best ways that retailers can show they care about their customers’ experience. New technology can help drive better outcomes for your customers, such as providing better service or an intuitive return process.

Real-time insights and machine learning are two of the easiest and most important technologies retailers can use. These allow retailers to track patterns of shopper engagement to predict new behaviors and offer more dynamic and personalized service every time they visit a website.[ix]

Another way to stand out is to provide great customer service across channels. This might involve using technologies like chatbots to bridge the service gap between digital and physical stores or enabling customers to see in real life what they were browsing online. Taking things a step further, some innovators are incorporating IoT and virtual and mixed reality into their store experiences. For example, in-store beacons can detect what customers looked up online and reflect related offers on digital signs.

It’s clear that there’s a lot retailers can do to improve their personalization approach and boost customer engagement – and that’s where a personalization solution comes in.

Plexure can help

Doing retail personalization the right way is difficult, but Plexure delivers the tools to make it possible. The Plexure platform uses cloud analytics to combine static and temporal data to uncover trends. The Plexure Analytics Engine and Power BI dashboards help surface key metrics such as campaign performance to support continual process improvement. Plexure’s solution helps retailers optimize customer engagement and loyalty and increases revenue and ROI, bridging the gap between digital and physical stores once and for all.

Try it yourself

Want to learn more about Retail Personalization? Try the solution for yourself at www.AppSource.com today.

LinkedIn: ShiSh Shridhar

Twitter: @5h15h


[i] https://www.infosys.com/newsroom/press-releases/Documents/genome-research-report.pdf

[ii] http://www.chainstoreage.com/article/study-retail-personalization-efforts-not-connecting-shoppers

[iii] https://www.infosys.com/newsroom/press-releases/Documents/genome-research-report.pdf

[iv] http://www.digitaltrends.com/social-media/why-consumers-are-increasingly-willing-to-trade-data-for-personalization/#ixzz2g8dgrqko

[v] https://www.infosys.com/newsroom/press-releases/Documents/genome-research-report.pdf

[vi] http://cdn2.hubspot.net/hubfs/497568/Ebooks_(new)/The_Foundations_of_Personalization-1.pdf?t=1477736478014

[vii] http://www.retailtouchpoints.com/features/special-reports/retailers-seek-innovation-in-personalization

[viii] Retail Insights, Microsoft, 2015

[ix] Kibo 8 Mistakes, 2016