a woman counting money
What's the common denominator between all elements of digital transformation? Data PHOTO: Niels Steeman on unsplash

The buzz around digital transformation is only getting louder. 

In his digital transformation trends list for 2018, analyst and Forbes contributor Daniel Newman lists edge computing, a continuing emphasis on analytics and a movement to 5G speeds in the mobile world among the forces shaping the future. While all fall under the overall digital transformation topic, the foundation for all of these is more elemental: data. Newman specifically cites IoT and the data it generates specifically as a driving focus for these futuristic digital capabilities. 

In terms of data-driving focus, I wholeheartedly agree. The digital transformation conversation is fundamentally about data: how we recognize new sources, how we prioritize the importance of all sources and if we can figure out how to use data to shape the customer journey. Why is that? Because we have more data today than most of us know what to do with. Statistica posits that by 2021, worldwide mobile data is expected to reach 49 exabytes per month. Cisco suggests that data created by IoE (Internet of Everything) will reach 507.5 zettabytes by 2019, and IDC estimates spending on IoT will reach $1.29 trillion by 2020.

Instant Gratification and Immediate Response

“If we have data, let’s look at the data, if all we have are opinions, let’s go with mine.” ― Jim Barksdale, former Netscape CEO

These data volumes can be overwhelming. Smart companies, data stalwarts like Walmart (tops on the NRF 100 retailers list since the list began in 2008) and tech titans like Amazon and Google, are figuring it out. And as they do it raises the bar for the rest of us. 

Take Walmart as an example. Its technology subsidiary, @WalmartLabs, rivals any Silicon Valley firm when it comes to using data to drive digital transformation. Dynamic store maps, mobile check-in for advance order pick-up, prescription management on-the-go, product registries and futuristic search-my-store capabilities are just a few of the omnichannel innovations designed to “bring experiences to life” for customers. And customers are responding. 

Multichannel experiences like those provided by Walmart, as well as the variety, delivery speed and convenience that Amazon facilitates, have unquestionably shaped our expectations as consumers. Shaped them towards instant gratification and immediate response. We expect to be able to look up product reviews and alternate pricing options while standing in physical stores, we expect timely answers to tweets aimed at companies especially when we are experiencing problems, and we expect communications to be relevant to our immediate situations. 

Combining these raising expectations with the myriad of new digital data being generated almost continuously means one thing to me: companies today have the power to use this data to know customers much more intimately than ever before. And any company that doesn’t figure out how to incorporate this treasure trove of data into their digital transformation runs a big risk of being left behind.

Value Hides in Unexpected Places

Few would disagree that data generated by IoT, digital and mobile yields value, not the least of which is our ability to provide the immediate response demanded by our customers. The cautionary tale, however, is to ensure we don’t lose sight of the inherent value in other types of data, the non-shiny objects, the data that paints a longer-term picture of the relationship that we have with our customers. 

A Forbes survey, “Data Elevates the Customer Experience,” asked respondents which data sources are most essential for customer intelligence and yielded a broad range of data which group into the following five categories:

  1. Customer Profile (CRM) — Call center interactions, email and direct mail contacts, product ownership and transaction history, name address, contact information, in-store interactions.

  2. Demographics and/or Psychographics — Age, gender, income, children, marital and employment status, education, attitudes, lifestyle, preferences, etc. (usually purchased.)
  3. Web and Mobile — Sessions, pages, referring sites, viewed content, commerce, app downloads, navigation, time spent, frequency of use, abandonment, feedback, email, etc.
  4. Social (Facebook, Twitter, Pinterest, etc.) — Social network and influence data, and profiles, work history, group memberships, product and company associations (likes or follows), online comments and reviews, VOC, etc.
  5. Beacon and Sensor (IoT) — Location, GPS, proximity, biometric (Fitbit,) RFID, product sensor, etc.

Aspects of the customer profile data (purchase and transaction history, call center and email interactions), as well as customer demographics, ranked right up with web and mobile as the most valuable data types. This result may surprise people, particularly digital natives, but it shouldn’t. It is the profile data that provides relationship context — highlighting the myriad of ways in which the customer has interacted with the company, the breadth of products purchased and how those products have been used. 

While social data absolutely helps to provide personal context, to illuminate a customer’s attitudes, preferences and relationships, those mean little without the relationship history to which the personal context should be applied. And while the mobile, digital and IoT data pinpoint real-time situational context, identifying the moments of now when a real-time reaction is needed, those reactions must be specifically tailored based on the preferences and historical interactions stemming from relationship data.

The bottom line? Data will be the currency that drives successful digital transformation.