Tapping Into One-to-One Communications With Mobile Apps, Personalized Pricing
It may be hard to put a price on loyalty, but thanks to mobile technology marketers can now put a price on personalization – and put personalization into price.
In fact, among the key strategies for using data to enhance one-to-one communications, the two that stand out most to me are mobile payment apps and personalized pricing. Or, to be more specific:
- Using mobile app data to deliver real-time offers that can engage customers at every point along the path to purchase – from home to checkout.
- Using data analytics to make better pricing decisions on a customer level.
For marketers, these strategies, done well, can represent significant differences in basket size and customer frequency. Timing, however, is crucial. More than one-third of U.S. shoppers have downloaded a food or beverage app in 2013, according to the National Grocers Association. One-third may not seem like a lot of the population, but that represents a 235% increase since 2010.
Fortunately, and thanks to emerging technologies, each of these strategies can enable the other to be more effective. Let's explore how.
These days, merchants do not have to wait until a purchase is made to send the customer a special promotion; offers can be made in real time right in the aisle. This means that those merchants that have not yet adopted mobile apps risk losing market share.
Forty-two percent of all mobile sales generated among the top 500 mobile-commerce merchants in 2014 took place through an app, according to the 2015 Internet Retailer Mobile 500 report, which gauges the industry. It is not surprising, then, that two-thirds of retailers planned to increase investments in mobile strategy and/or app development by more than 5% in the fourth quarter of 2014, according to Forrester.
The investment underscores the degree to which apps engage consumers and encourage increased purchases. However, our own internal research into mobile app use among grocery chains revealed that many lack loyalty card or shopping history integration. This is a costly oversight, since the data collected through a loyalty initiative would provide a highly customer-specific understanding of preferences and needs.
In addition to tracking product purchase history, which merchants can do on their own, a loyalty-based mobile app can enable retailers to collect data regarding location, user settings and in-app selections. This additional data can inform a number of one-to-one marketing initiatives.
For instance, through a loyalty app’s unique identifier, a merchant can learn a particular shopper’s in-store browsing patterns and anticipate her needs.
For example, if a time-starved mom is passing the baby aisle, she can receive information on a great sale on diapers and healthy convenient meal options in the frozen aisle. Through the use of predictive data analytics, the merchant can further see that this shopper typically buys organic produce and heart-healthy items rather than salty snacks. Knowing that shoppers who regularly purchase both organic produce and heart-healthy items tend to spend more – and look for value, tips and ideas–the merchant can additionally send recipes with coupons for the ingredients.
These examples illustrate a key feature that sets mobile apps apart from other forms of marketing – it provides a picture of the consumer’s shopping journey in context, so merchants can communicate in a timely manner both in-store and out of the store.
The data, meanwhile, can enable the merchants to create and send one-to-one communications including offers, fliers and shopping lists that include items the shopper regularly acquires. The analytics also equip them to offer products with personalized pricing.
Personalized pricing is more about making favorites than playing favorites. It is the practice of tailoring prices according to demand, consumer behavior and competition. With the help of a mobile app, a merchant can personalize an offer in real time, sending limited-time specials on items relevant to a particular shopper.
Retailers ranging from Kroger to Amazon.com use shopper data to identify the products for which customers are most interested in receiving discounts. And consumers are responding. Almost 70% of shoppers (67%) said they most value money-saving offers in their smartphone apps, according to 2013 research by Adobe Systems Inc. Almost seven in 10 (69%) said company emails most influence their purchases.
Typically, such personalized offers are determined at the customer segment level, meaning all customers in a particular segment receive offers for the same products. But with a mobile app’s integration and the right analytics, the offers can be optimized to the individual customer and update dynamically as customer preferences change. Using their loyalty program data as a guide, retailers can send electronic coupons via an app to a customer’s mobile phone, incorporating time of day or location into the delivery. (Shoppers can redeem these offers by scanning barcodes or QR codes at the register.)
Further, the customized offers can be designed to reward shoppers for brand loyalty. A program can send a customer who uses a personalized discount an invitation to a limited-time shopping event, or it can simply reward her with double points.
Let’s consider the shopper who approaches the freezer case as an example. Say the shopper is a new mother short on time but willing to make health-conscious meals. Her local grocer can identify her propensity for health, convenience and value. However, in addition to fresh fruit and low-fat dairy items, she occasionally purchases premium ice cream. In addition to offers for the foods she regularly buys, the grocery can send her a special price on ice cream via mobile app when she nears the freezer case. Additionally, because the grocer knows when this shopper last purchased diapers, it can trigger mobile offers for when she is likely to run out, along with coupons for complementary items such as wipes.
The best part of the personalized story – competitors can't easily copy the strategy because they can't see it. That's game-changing.
Matching solutions and shoppers requires a few foundational tools. Following are three key steps for using mobile apps to customize pricing and communicate more effectively with individual customers:
Use best data, not big data
Predictive analytics are essential for a mobile app to effectively personalize the customer experience. An app that captures the necessary customer data involving product preferences, lifestyle indicators and context will inform the merchant of what its customers really want, and what they really want the app to do.
A mobile app, if expected to deliver one-to-one communications and pricing, has to be treated as more than a competitive device. It should be implemented with specific, organization-wide goals in mind and then deliver against those goals. To this end, the app should employ one method of sign-in or identification across all customer channels, contributing to a single view of the customer.
Manufacturers already produce a lot of digital coupons, so they represent a natural partnership opportunity for merchants. By overlaying their individual customer insights, retailers and manufacturers can customize their offers based on individual buying behavior, resulting in communications that are more relevant.
The price of customer loyalty may be hard to quantify, but the tools to achieving it are increasingly accessible and affordable. Mobile apps, fortified with loyalty data, can deliver the pricing, and personalized communications, that turn quantity to quality.