Cutting Through Chaos in the Age of Mobile Me

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Cutting Through Chaos in the Age of Mobile Me

By Kevin Benedict - 01/25/2016
Increasingly, consumers are using multiple devices and different apps and websites across different locations and at different times of the day to do their mobile shopping. Often smartphones are used for quick,on-the-go searches and discovery; tablets for in-depth immersive product research, and laptops for purchases.

People even change their device preferences depending on the time of day and the price of the products they are researching. Mobile devices are popular in the morning, at lunch and in the late afternoon. Desktops and laptops are popular during business hours, while tablets are popular in the evenings.  

All of these variables and different views make it difficult for retailers and e-tailers to recognize and understand where consumers are in their path-to-purchase journeys, which makes it even more difficult to create personalized experiences, which 90% of 18-34 year-olds highly value.
 
Let’s consider a few additional variables. In a recent online survey conducted by Cognizant’s Center for the Future of Work, we asked participants where they were physically located when making online purchases, and the top five answers were:
 
  1. 46% in the living room
  2. 36% at work
  3. 29% in the bedroom
  4. 24% in the TV room
  5. 20% in coffee shops or restaurants
 
When asked the time of day they make most of their online purchases, participants listed the following in order of popularity:
 
  1. Early morning
  2. Mid-day
  3. Late night
 
These patterns, plus knowing relevant time zones, are important data points for companies that are looking to optimize mobile and online consumer engagements.
 
Google reports 79% of consumers now use smartphones to help with shopping activities. In a recent RIS/Cognizant survey of 5,000 North American consumers it was found that 56% use multiple platforms and mobile devices while shopping online. Among smartphone users, 82% research products and compare prices while inside stores. That means it is not enough to get customers in the doors of retail stores, because competition for sales continues in the aisles and doesn’t stop until the cash registers ring.
 
As a result of all these consumer behavioral variables many retailers are confused about how to best engage with the digital and the increasingly mobile consumer. Path-to-purchase journeys appear fragmented as customers approach from different digital directions and devices. These fragmented views cause missed sales and marketing opportunities. Many are operating as if “blindfolded” - unable to recognize and influence consumers on their path-to-purchase journeys.
 
Removing these blindfolds and other obstacles requires fresh strategies and updated business models. It also requires companies to design, implement and leverage new customer data-sharing partnerships. In addition, many businesses must upgrade their data collection, analytics and real-time information logistics systems to improve recognition, personalization and engagement. 
 
Our research findings identified five key recommendations for achieving success in mobile and online commerce:
 
1. Mobile consumers today are a market of “me.” For retailers, mobile consumers are not one homogenous market, quite the contrary. The millions (billions) of individuals who make up the market of “me” differ widely in their behaviors, depending upon their age, gender, technology preferences and education level. Recognizing the uniqueness and behavioral patterns of individuals, then personalizing experiences for each individual, requires a “Mobile Me” (MME) strategy - designed around the only experience a consumer cares about.

2. The mobile market is at the forefront of the “personalization vs. privacy” dichotomy. Mobile shoppers want the benefits of personalization without the downsides. They are willing to share detailed personal information and brand/ product preferences within loyalty and rewards programs, but hesitate outside of those parameters. This must be recognized and exploited in retail strategies. Companies need more (and better) customer data to improve personalization and relevance. This data should be collected and analyzed with the full knowledge and consent of the customer. We call these MME (Mobile Me) Data Partnerships. They are explicit agreements between retailers and customers — designed to mutually benefit from the collection and use of a defined set of personal data.

3. We recommend enterprises implement 3D-Me data collection strategies (three dimensional), which involve exploiting three data-rich sources for personalization initiatives: 
  • Digital: Mobile apps and websites
  • Physical: Wearables, smart products, IoT sensors, telematics, etc., that measure and monitor physical environments and objects
  • Personal: Historic and current data — personal, preference and transactional — volunteered by the consumer in MME data partnerships.
4. Personalization using 3D-Me data is a tactic in an incomplete strategy. Personalization presented out of context is trivia. Value is only realized when collected 3D-Me data is combined with contextually-relevant opportunities, moments and environments (CROME) to trigger a just-in-time MME experience. CROME triggers are meaningful bits of data that when captured and analyzed activate time-sensitive and relevant personalization activities. CROME triggers transform the potential value of personalization into kinetic value.

5. 3D-Me data collection strategies permit innovators to develop P&L (profit and loss) statements specific to individual customers. Achieving clarity on the economic value of an individual customer makes it possible for retailers to customize the rewards and benefits of loyalty programs for individuals both online and in store. Our Center for the Future of Work calls this 3D-P&Ls. Analysis of an individual’s 3D-Me data can provide the required information to generate accurate 3D-P&Ls, which can be used to customize loyalty programs. Consumers can use mobile apps and websites, or check-ins at physical store locations to receive rewards and benefits calculated in real time, based on 3D-P&L algorithms.
 
Retailers and e-tailers must recognize the importance of data, personalization and context, and prioritize initiatives to upgrade and improve all information logistics systems to support these new models and address changing mobile consumer behaviors.
 
Download and read the full report titled “Cutting Through Chaos in the Age of Mobile Me”.
 
Kevin Benedict is Senior Analyst, The Center for the Future of Work, for Cognizant Technology Solutions.