Data-Driven Consumer Engagement

Bottom Line

  • Consumer engagement tactics at large brands continue shifting from a retail-driven process, to an online and mobile media-driven process but a new massive data-driven consumer engagement wave is threatening to seize the day. 
  • This transformation is in full swing and laggards’ risk losing more market share than could ever be seized by the most talented and aggressive online and offline marketing campaigns of days past. 
  • This post makes the case for how vital data-driven transformation is for brand strategists and marketers and provides initial tactical pointers for those willing to ride this wave.

Challenged brands, victorious brands

Most CMOs have grown up with visions, evangelized by technology vendors, of an all-digital future where personalization of product and service experiences would dramatically increase consumer engagement. This one-to-one vision of the future combines the enviable economies of scale of automated mass-marketing with the high-margin potential of the personalized experiences consumers are loyal to and pay a premium for.

Take a look around: all of our needs are already addressed by an app, consumers and companies are over-equipped with connected devices and software, and most mainstream brands have digital channels of their own (online stores, mobile apps, web content, etc.) 

However, not all companies are succeeding in this data-driven transformation. Success is defined as a large-scale profitable rollout of the consumer product across all consumer channels at once. An example of a company that has done this well is Amazon, which has succeeded in overcoming daunting obstacles to implement truly data-driven product experiences and the underlying big data infrastructures they require. Amazon has also used their technology capabilities to innovate with digital marketing and branding practices (i.e. ultra-targeted campaigns, personalization of consumer experiences, massive social engagement, and platforms like Amazon Retail Services).

Brands equipped for victory

For brands newly pursuing a transformative data-driven strategy, there are some things to keep in mind:

  • Focus on your strengths, and leverage your existing assets: consumer relationships, data, brand equity, IT investments, and more. Diving into how to leverage those assets is a bit out of the scope of this post, but there is a large body of established frameworks and lessons learned and shared to draw from.
  • Be deliberate in building leadership to own the vision and drive changes. Chief Data/Digital Officers, Chief Innovation Officers are helpful leadership patterns to emulate but remember these positions are meant to be eliminated as the transformation is consummated and integrated into the organization.
  • Expect large and sustained investments to be needed. Such a data-driven transformation will challenge your IT strategy, organization and a number of other functions in the organization. Develop funding plans for the investments to guarantee sustained momentum.
  • Like with any large project, define key milestones, which various parts of the organizations can target as strategic progress mileposts.
  • Mobilize people to endorse the vision of change and execute on it. This is as much a cultural and organizational shift as it is a technological one. As Thomas Davenport predicted in his renown Competing on Analytics article, fostering a “’test and learn’ culture based on numerous small experiments”.

Out of that list, let’s start by looking at the data that companies already have access to, and why it is worth paying attention to.

All consumer engagement roads lead to data

Many companies struggle with how to use digital capabilities to materially increase consumer engagement, not just amplify their digital presence.  For example, turning an early mobile app success into a repeatable and growing engagement success requires cooperation across your company’s divisions and functions (product design, marketing, retail, etc.), culminating into new data-driven practices and capabilities. These practices and capabilities will help ensure predictable customer engagement outcomes.

Looking at digital groundbreakers like Amazon, we see that this company invested large portions of their profits in engaging their customers and other consumers in every way possible. This platform strategy led it to invest significant funds into new fundamental business capabilities like mobile devices (Kindle e-reader, tablets, streaming boxes, mobile phone), services (Prime) and content (HBO partnership, streaming platform). Ultimately, though, much of the value of the platform effect comes from the integration of all these customer touch points through data and analytics. Interestingly enough, this integration at Amazon led it to develop its own critical cloud technology capabilities, which also eventually became a new business unit of its own: Amazon Web Services.

To achieve these same customer engagement competitive advantages, your company must achieve this same integrated brand experience. The process can understandably be costly, risky, and painful because organizations must make way for new business practices with some amount of creative destruction. However, to weather the stormy seas of disruption and innovation, you are uniquely positioned with valuable assets newer brands rarely have easy access to data about the market, customers and consumers, investment capabilities, existing technology assets, extensive brick-and-mortar presence, etc. 

An example of a more traditional mainstream brand pursuing engagement through innovation rooted in data integration is Target. Target’s online retail operation really only became strategically successful as a key competitive advantage against the likes of Amazon when it pursued its omnichannel strategy, allowing customers to order seamlessly any item from anywhere. In the store, online or through an app, the company built a groundbreaking capability to allow sales staff and customers to order products regardless of whether they sat in a store aisle or an online retail distribution center. Such a capability was transformational since it required almost every functional area at the company (store operations, online retail, procurement, distribution, logistics, finance, marketing, IT and more) to share data, collaborate towards, and ultimately transform into the omnichannel pioneer Target became.

In a world where any small business can claim a global pulpit to speak to all consumers at once and where wealthy technology companies are using their knowledge and reach to displace traditional brands, those traditional brands have no choice but to wager all their unique assets (customer relationships, data, brand equity, IT investments and more) to compete in the omnichannel global market.

Data is the key to devising these more integrated brand experiences. Stitching the ever-growing stream of digital consumer data with relevant business data from ERP systems to obtain a complete map of the customer journey presents significant engineering and data science challenges. However, this is how brands can truly customize the experience for each customer based on their past interactions and what the brand knows about them. It also requires more customer insights than traditional analytics or detailed customer profiles can hold. Data science models can provide decision makers, personnel, and software applications with the foresight to offer customers the experience and offerings they desire the most before they disengage or experience dissatisfaction.

Achieving this today remains a massive technological challenge that no vendor solution or collection of solutions can address alone. Organizations, including consumer brands, often require outside help or internal disruption strategies to navigate this transformation.

The first step in the journey of driving brand engagement with data is to understand, concretely, the changes your organization will be facing in order to truly yield strategic competitive advantages.