Thinking Small to Re-Envision the Future of Customer Apps and Big Data


Big Data is being re-examined for its role in powering data-enriched customer apps.

Harnessing the power of Big Data is all the rage. And with good reason, given the potential to turn large volumes of data into game-changing market insights and strategies.

So it’s not a surprise that Big Data spending is expected to hit $50 billion by 2017 according to the latest market forecasts, and more than 60% of organizations (with $1B in revenue) have active Big Data projects according to a recent survey.

Yet, it may be time to start thinking “small” when it comes to big data. Small in terms of the approaches and design perspectives that are about delivering actionable insights and answers to the broadest possible audience.

Even as many organizations strive to gain competitive advantage and better serve their customers by integrating and analyzing (and even sharing) their Big Data assets, several challenges emerge when it comes to delivering insights directly to customers and customer-facing staff:

  • How to access the ever growing volume and diversity of data sources relevant to an organization’s internal business users, when most traditional BI systems/approaches are more suited for “batch” processing of largely transactional data without access to new Web/social/mobile data?
  • How to manage/secure data assets and present large volumes of information to a large volume of end-customers in a highly consumable, engaging fashion (as a special type of Customer Experience Management or “CEM”) via both online and mobile delivery channels?
  • How to deliver these capabilities to everyday business users and end-customers (who aren’t data scientists) with zero training, to help them perform everyday tasks like targeting a new campaign, understanding churn rates, tweaking an investment portfolio, or projecting next month’s sales commissions?
  • How to merge (or at least begin to) the management of customer experience with the delivery of meaningful data-driven insights to end users. Customer experience today doesn’t just revolve around how effective it is to interact with an organization. It’s also increasingly linked with customers’ individual personal business and lifestyle data.

These challenges, along with the success of consumer data-driven apps, like Amazon’s product recommendations or Nike, in delivering Big Data insights in simple, smart ways, have inspired a number of us in the industry to re-examine the state of Big Data, and more specifically its role in powering data-enriched customer apps.

In fact, this thinking has moved into the spotlight over the past 18 months as part of the small data movement (driven by the design principles: make it simple, make it smart, be responsive, be social) I’ve helped to advance via my research, blog, and sessions at various industry events.

The movement is not only about shifting focus to the “last mile” of Big Data, but also the approaches and design perspectives that support the delivery of relevant insights and answers to everyday users. As we’ll explore below, this perspective can also help us re-envision the future face of both customer apps and data, as well as the tools that support the creators of those data-enriched customer experiences.

The Future of the Data-Driven Customer Experience

As data and insights play an increasingly important role in the end-customer journey, brands who tap the power of big data to better connect, inform and motivate their customers at each step have an opportunity to gain significant competitive advantage. Yet, this starts with a foundation that enables us to access, manage, and deliver today’s customer data in a form that fits the needs and skills of every user.

Building on our small data philosophy and definition, a series of design criteria/questions emerge for these types of customer “Data-enriched Customer Experience Apps”:

1. Are all relevant data sources accessibleAre we able to deliver large volumes of new and historical individual data to each user on a regular basis? Are resulting customer apps accessible in the broadest sense—by being available to all regardless of role, location, or physical ability?

2. Is data presented so it is understandable (and not overwhelming)? Can we enable (non-technical) users to access relevant data as a report, dashboard, or data export? Are we personalizing the experience by account, role, or user segment? Can users easily navigate and explore their personal data, and access other sources from within the app?

3.  Are we being helpful and delivering actionable insights? Are we packaging insights and answers to support everyday tasks? Can users easily annotate, and share learnings from their session? Can support teams seamlessly monitor the customer experience and help out as requested?

The Opportunity

With ubiquitous computing driving more customer choice, effective delivery of individualized insights will be the differentiator for more brands in 2014 and beyond. In many cases, personalized data will define the brand experience, especially where we have a large volume of both users and insights from disparate sources, that need to be presented in a highly consumable fashion to everyday users (think asset management, healthcare portals, premium content services etc.).

In this environment, scalability and smarts, plus a zero training interface and visual tools, are critical to delivering time to value, as well as experiences users will want to explore and share with their peers.


OpenText is the leader in Enterprise Information Management (EIM). Our EIM products enable businesses to grow faster, lower operational costs, and reduce information governance and security risks by improving business insight, impact and process speed.

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