Customer Experience Lab

3 Customer Experience Improvements Retailers Can Use to Cash in on Millennials

By Joe Novak on December 20, 2017

 

Many retailers are finding it difficult to connect with millennial shoppers. Even when able to sell to them, they are often unable to sustain the relationship. Findings from Centriam’s 2017 Retail Study confirm this: millennials are more price sensitive, less likely to repurchase, and 40% more likely to be detractors. [Click to Tweet]


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Given these difficulties, how should retailers interact with their millennial consumers? My previous blog discussed the best method for driving down detractors—making shopping easier—this blog expands on that idea and applies it to millennials.

Millennials less likely to recommend

While millennials are more likely to be detractors, they still respond to great customer experience. Millennial passives are 40% more likely to repurchase than millennial detractors. And while millennials are already spending $600 billion annually, by 2020 Accenture projects them to generate one third of all retail spending, at $1.4 trillion. This makes it imperative that retailers consider how best to sell to them; and making shopping easier should be a priority.

 

Centriam Retail Customer Experience

Download Centriam's 2017 Retail CX Survey to uncover the connections between customer experience and profits!

 

Uncover the connections between customer experience and profits

Embracing millennials will grow your business, but what does it really mean to make shopping easier? Here's three ideas:

  • Mobile first, but with a chatbot.

    Many millennials are mobile-first customers, and chatbots have proved an effective communication tool. Chris Messina of Uber has coined the term “conversational commerce” to describe this phenomenon. North Face uses IBM’s Watson to make item selection easier. Macy’s chatbot works in store to direct shoppers to the desired department, and Taco Bell even integrated a chatbot into Slack, the popular messaging application. 
  • Omnichannel needs to extend to the transaction.

    Millennials also desire seamless interactions across channels, so many retailers are making purchasing easier by experimenting with omnichannel integration. REI’s emails use “deeplinks”; when customers click on a link, it will open automatically in the REI app. The app then finds the nearest store with the item in stock, and allows for the customer to reserve it. Another popular method is buy online, pick up in store. The Starbucks app is a great example of this, allowing customers to order ahead and pick up drinks at the nearest store.
  • Machine learning predictions lower transactional friction.

    Machine learning is a great customer experience tool when it anticipates customer needs. This is more than product recommendation engines, which are generally evaluated by a different KPI. For example, Wells Fargo ATM’s learn customer preferences over time and use large green buttons for the most commonly requested items of each unique customer. Similarly, Nest learns your heating desires and how they vary by time and sets your thermostat appropriately. These examples may only save seconds, but those seconds saved are addictive and secure loyalty from your customers.

Download the whitepaper: Centriam's 2017 Retail CX Survey

However, you choose to engage with millennial shoppers, great customer experience is the key to building lasting profitable relationships. My colleague Joe plans to share some thoughts on creating more millennial promoters in an upcoming blog.

 

Topics: Retail Customer Experience

Author: Joe Novak

Joe is committed to improving the ability of Centriam’s clients to act upon data and insights. Joe brings diverse experience utilizing data and advanced analytics to improve performance across many industries. Prior to Centriam, Joe managed risk for multiple credit card and auto loan portfolios at US Bank. Joe also worked in marketing analytics at Target and survey analytics for the Minnesota State Colleges and Universities system. Joe holds a B.A. in mathematics and computer science from Macalester College and an M.S. in applied mathematics from the University of Colorado.
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