Data has claimed top priority in CXO discussions, especially for the potential to build unique and engaging customer experiences or carve out a distinct competitive advantage.
The data universe is expanding into diverse forms, each becoming richly populated every minute in its own right. IDC in its Worldwide Global DataSphere Forecast 2022-2026 predicts that the global datasphere is set to more than double from 2022 to 2026. By 2026, the world’s data will collectively grow to scale 220 zetabytes (ZB).
However, many data-rich organizations sit at the fulcrum of an interesting conundrum. They are home to an ever-increasing mountain of data but a significant portion of this data remains unutilized. As per Seagate’s Rethink Data report, organizations fail to leverage 68% of data available with them, putting only 32% to work. This ‘dark data’ or data that is routinely collected but not used for analysis to draw insights, only adds to technical debt.
Traditionally data-rich sectors such as banking, financial services and insurance (BFSI) and consumer packaged goods (CPG) are overcome by the DRIP syndrome – Data Rich, Information Poor. With 80% of data considered unstructured and therefore left untouched in the absence of the right tools, these incumbent behemoths sit on enviable data stockpiles. The key is to leverage the right technology and tools to ‘get data to talk’.
Dark data – what is it?
Gartner defines dark data as ‘information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes, such as analytics, business relationships and direct monetizing.’
This includes:
- Internal data gathered from BAU activities lying dormant in storage
- Unstructured, non-traditional data commonly referred to as ‘digital exhaust’
- Deep web data
Prime examples include:
- Customer interactions
- Media data such as video, image, social accounts
- Video surveillance footage
- Market research
- Data related to financial transactions
- Sensor data
- Website logs
Getting data to ‘talk’ starts with harnessing every source
The potential of data that exists across the organization is largely untapped because it is neither fully organized nor, as in most data gathering exercises, even taken complete stock of (which is the case with dark data). This often leads companies to turn a ‘blind eye’ to the enormity of data they call their own, how and where it can be found, how it can be useful to draw meaningful insights to engage in myriad and impactful ways with customers.
Take the case of BFSI; legacy insurance providers may have had access to customer data on preferences, stages of life that they are likely to want insurance at, and they even had the lead on customer trust. However, by not tapping into this data using technology, they lost the opportunity when online insurance aggregators made it easier for customers to get competitive insurance at the click of a button. The same applies to banks – where there is a trusted relationship already in place, anticipating opportunities like loans during the life of their customers are missed out.
Tapping into these vast data stores can offer limitless possibilities to engage with customers and create a host of new experiences as part of their customer journey.
With traditional companies that have grown vastly in pre-digital times, mapping out the all the possible sources and formats of data can be a mammoth task. Dealing with complex organizational structures, regulation and compliance among various business and product lines, and data housed in various sources and in a variety of formats are only some of the challenges the need to be overcome. Yet, such industry behemoths are well-placed to take on these challenges, having demonstrated commitment to customer-centricity and business growth over time.
Challenges to be addressed by legacy industry leaders setting out on the data quest
The biggest challenges for incumbents to overcome while on the path to harness data are:
- Humongous unstructured data volumes and their categorization given the diversity
- Incomplete and biased data compromising data quality, authenticity, and reliability
- Lack of the right tools and methodologies to track, capture, filter, structure, and validate the data
- Concerns regarding data privacy and ethical data capture and use
- Shortage of experts with the ability to qualitatively and quantitatively analyze social data in the right context given its limitations
- Absence of a common framework to integrate customer data across multifarious traditional and social channels
- Not budgeting for a clear, long-term data analytics strategy for social media and governance
- Greater exposure of such large datasets to cyber risks
Putting in place a data strategy can put focus on customer value, the greatest driver of business growth. By working with technology and data experts, companies can overcome the challenges of technology and integration and target aggressive growth and sustainability by exploring deep, layered, and diverse relationships with customers.
Using AI to leapfrog over organizational complexities in deriving value from data
Big data technologies bring the biggest advantages for sectors like BFSI, with the ability to easily process and harness insights from structured, unstructured, and semi-structured data lakes towards the goal of customer delight.
Cognitive systems - the triad of natural language processing, machine learning, and artificial intelligence – can help proactively drive unique customer experiences rather than taking a retrospective approach. Of late, a proliferation in API services has allowed fintech to make the best use of unstructured data by letting cognitive systems take a shot at them. The good news for legacy companies is that for this purpose, neither do all the systems need to be unified and cohesive, nor do they need to be uniform to deliver insights. The biggest advantage is that deep learning need not be an internal capability.
Incumbents can leverage the power of analytics tools alongside ML and engage experts to train the system. Moreover, enterprise search criteria should aptly cue in an accurate reading of user intention, behavioral observation, and subsequently detecting patterns rather than mere keyword search inputs. This can open up a whole new world of possibilities for these data-rich enterprises by enabling a rich, layered, novel, and evolving customer experience.
To illustrate, let’s look at an example. Customers routinely find IT service to be a tedious process – right from tagging it to the right service category to receiving timely advice and query resolution. Incumbents can engage cognitive search tools that structure together tickets with similar reasons or phrases to get it right every time. Such automated routes can easily make query resolution more efficient in terms of time taken and costs. The system can go a step further to chart out trends, pick out anomalies in capability planning, thereby enabling better resource management. The next step would be to have chatbots that work in conjunction with these tools to provide the customer with immediate assistance and personalized recommendations, reducing dependency on human agents.
Embracing big data to cater to new customer demands
For brands to truly stand out, sticking to the traditional will no longer make the cut. Catering to new-age consumer demands involves thinking a step ahead of them. This definitely calls for embracing big data tech and AI tools as enablers to create brand experiences that are dynamic and add unique nuances to a customer’s journey and reinforce the relationship of trust.
Working with technology partners like Decimal Point Analytics, which offer expertise in structuring data programs for BFSI, CPG, and other sectors can help legacy companies simplify the task of harnessing data across the complex organization. Use of algorithms and technology takes productivity and efficacy to levels usually unseen in traditional research setups.
The future path with data is inevitable, and traditional companies have the edge when it comes to data authenticity and quality. All they need to do is build the right set of technologies to leverage their customer data, and lock in customer loyalty for life.
