Keeping Customers Loyal: Creating Experiences Powered by Data

por Admin Popai Spain,

In 2017, many struggling retailers closed their doors. In fact, more than 6,800 stores closed from the impact of online retailing or, in some cases, lack of interest in their businesses. Consumers are no longer willing to go into a store and meander through the aisles to make a purchase, unless it’s for a bargain (think TJ Maxx and Ross Stores). They have, however, a greater appetite for a more unique and curated shopping experience that aligns to their tastes and lifestyles. While many retailers have understood this shift in consumer behavior for some time now, they've been slow to react. This means 2018 will be an important year for retailers to continue to enhance customer experiences and sharpen digital retailing skills.

Personalized Engagement is Tablestakes

Experience shows that customers are willing to spend more money when a retailer “knows” them and their recent purchasing and browsing activities, and can offer a unique and personalized experience.

Segment, a data marketing company, surveyed more than 1,000 shoppersand found that customers have high expectations of online, big-box and department store retailers when it comes to personalizing interactions. However, the reality is that niche retailers, because of their focused offerings, are far more successful in providing these sought-after experiences than larger retailers and their broad product mix. The same survey showed that personalization can lead to higher revenues and increased customer loyalty, as 44 percent of customers will shop with the retailer in the future. A failure to provide personalized experiences has been one of the main reasons department stores have been shuttering across the country and must double down on efforts to reach their customers in more engaging ways.

Use Technology to Drive Loyalty

Technology is playing a critical role in keeping customers’ attention. Augmented reality (AR) and artificial intelligence (AI) capabilities are increasingly becoming mainstream for driving personalized customer experiences. For example, the beauty industry has begun to use AR to help shoppers better understand how specific products will look on their skin without having to leave their homes or even apply the cosmetics to their faces. Not only is this good for the customer, but it also allows companies to understand what products a customer is interested in so they can offer relevant discounts and upsell similar products in real time. Additionally, AI capabilities are being deployed as online chatbots can help answer simple questions quickly, freeing customer support reps to handle more complex issues.

Related story: Why Business Agility is the Key to Increasing Retail Growth

According to an Accenture study, 82 percent of customers that have switched loyalties from one retailer to another are on record saying a better customer experience would have “prevented a switch.” Bottom line: Customer experiences, whether good or bad, leave a lasting impression and influence future behavior.

Data Fuels the Customer Experience Engine

How are companies creating the kind of retail experience across all channels that keeps customers coming back? Simple. It’s data.

By leveraging data such as purchase history, click stream and results from marketing campaigns, you can triangulate who your customers are and what they may be interested in. Overcoming the challenge of accessing this data in an efficient manner is also straightforward. Many retailers have invested in data management competencies and solutions to help develop and execute against data strategies that are enriching their customer experience programs.

The first step to creating greater personalization is to identify your customers — e.g., who they are, where they live, how they like to shop, if they are part of your loyalty program — by gathering data across business units and sales channels. Next, enriching customers’ profiles with information from websites, social media and point-of-sale transactions can improve customer segmentation analytics, helping drive more informed marketing campaigns. Machine learning is making these insights more actionable as data flows through AI engines and provides sales, marketing and product development teams with information that can be quickly tested and adjusted on the fly. Now, regardless of where the customer is shopping — in-store or online — your sales associates and websites can better curate products to fit the customer’s need.

This same data, along with customer feedback and support information, can be used to feed technology investments that help improve both in-store and digital experiences. For example, using transaction history and AR technology, Lowe’s has created an in-store navigation app that can help customers quickly find the items they're looking for, while recommending other products based on previous purchases.

As you continue to collect more and more data, you can use it to create products and experiences more in line with your customers’ lifestyles and needs. You must continue to focus on better understanding your customers to reduce the risk of nimbler, more data-savvy competitors stealing their attention.

Hamaad Chippa is the director of industry consulting at Informatica. Hamaad is responsible for identifying data management challenges, trends and best practices in the manufacturing, retail and CPG verticals.



Para comentar, por favor inicia sesión o crea una cuenta