The importance of data integrity cannot be overstated. It’s not just a matter of maintaining clean databases; it’s about unlocking the true potential of your enterprise’s most valuable asset—data. One remarkable aspect of investing in data integrity is its profound impact on customer satisfaction.

According to a June 2022 Spotlight report by the IDC, investments in technology to improve data integrity have positive impacts on a wide range of business metrics, with customer satisfaction topping the list of improvements at a significant 42% improvement.

Improving the integrity of data requires actionable data intelligence that increases the transparency of data – by creating context – and enhances data quality through repeatable processes and by enriching internal data with trusted external sources.

But how does improving data integrity directly affect customer satisfaction?

Break down data silos.

The size and complexity of most large organisations mean that these businesses frequently break up operations into smaller business units, subsidiaries or even product/brand-focused groups.

This makes sense – smaller units are more agile, are easier to measure, and can cope with different operating procedures or systems that may be necessary to drive what may be, in some cases, very different businesses.

However, for a customer dealing with this enterprise, across a range of business units or product portfolios, this can mean a very disjointed and inefficient experience. A simple example, marketing from one business unit may continue even after the customer has requested marketing to stop from another business area.

Or a customer may be asked to update the contact or banking information by multiple business areas – leading to an annoying and inconvenient repetition of effort….

In the worst-case scenario, a customer with a longstanding, and profitable, relationship with one business area, may be treated poorly by another business area where they do very little business, due to a lack of visibility of the customer’s total value to the broader enterprise. This can lead to them churning out their higher-value business.

What is efficient at a business unit level can be inconvenient, or even, create a negative experience for a customer dealing with, and expecting a consistent experience, across multiple business units.

Breaking down these business silos can help the business to gain a better understanding of each individual’s footprint across the total enterprise. By helping each business unit understand the customer’s preferences and footprint, the enterprise can ensure a more consistent experience that is aligned with the customer’s preferences.

Breaking down silos can also help us to improve how we communicate with customers, particularly as we make the shift from face-to-face interactions to digital channels.

From multichannel to omnichannel

Almost every business, of any size, is now interacting with customers across a range of digital channels, including our websites, our call centres, mobile channels, social media platforms and our on-premise experience.

The Covid-19 pandemic accelerated the adoption of digital platforms, both by consumers unable, or unwilling, to travel to traditional stores and by businesses looking to find new ways to connect.

The speed of adoption, particularly of new channels, can lead to disjointed experiences.

For example, a customer may spend some time on a website, interacting with a chatbot, before making the decision to call a call centre to finalise an order or deal with a problem. In many cases, the history of the previous interaction may be lost, and the customer is forced to repeat the entire call.

Breaking down channel siloes moves us from a multichannel capability – one where the customer may choose to interact with us via any number of channels, but where each interaction is treated on its own merits – to a truly omnichannel capability – one where each interaction is shared for future reference and knowledge is not lost.

This was a key opportunity realised by the Norwegian financial institution, DNB Bank, as they reinvented themselves as a customer-centric digital bank. DNB approached specialist data integrity vendor, Precisely, for data quality solutions to manage the challenges and opportunities created in the business by the explosion of data brought by digitisation.

“Everyone talks about going digital, but if you’re not capitalising on data streams that are generated through your digital channels, then you’re going digital without listening. My role is to leverage digital interaction data to reconnect and stay relevant to our customers on digital channels.”

Aidan Millar, Chief Data Officer at DNB

Of course, this avalanche of data also creates opportunities for data-driven marketing.

Personalisation

Not only do customers not respond to blanket attempts to sell them products that they do not want, but they can also actually drive existing customers away. Conversely, research shows that companies that excel in personalisation generate 40% more revenue from those activities than average players.

“If there is anything that the past year has taught us, with a pivot to distancing and digitisation, is that personal, tailored experiences really matter, in banking and just about everything else.”

Lori Beer, CIO, Morgan Chase

The ability to deliver what a customer wants hinges on the ability to understand the customer in the first place. Data analytics is therefore the key technology for improving CX across all touchpoints. 

“Data is key,” explains Quinton McKenzie, Sky TV New Zealand’s Head of Corporate Core. “It really allows the understanding of your business and your customers, specifically within our industry. Customers want to be talked to personally, the days of sending out blanket emails or comms or even putting customers into segmented groups is gone.”

As companies push into new ways of using data and creating insights about customers, the real challenge is ensuring that you have high-quality data, especially if you want to leverage data to drive personalisation.

All data is big data

Big data was a term coined by Doug Laney in to describe data that is growing rapidly (Velocity), comes from many sources(Variety), and has high Volumes. Five or six years ago, this may still have meant a subset of data within the enterprise.

Today, the thirst for data has grown exponentially, and that means broader datasets, alternative data and deeper history. Almost all data exhibits one or more of these “big data” characteristics.

“Current events drive people to look for insights in areas they haven’t needed to in the past. Whether investment firms are analysing cargo ships stuck in port, satellite imagery of shopping mall parking lots, or consumer sentiment metrics captured on social media, the ability to leverage these new data sources is key to hedging risk and having first mover advantage on investment opportunities,”

Spiros Giannaros, President and CEO at State Street’s investment technology firm Charles River Development.

“How can I get better visibility that I don’t normally gain through my standard datasets? It is causing people to look a little bit broader than they typically would.”

The old adage of “garbage in, garbage out” still applies, only on a larger scale.

Companies must deliver data integrity at scale, across vast data sets and across data landscapes that bridge both on-premise and cloud architectures. This has led firms, like State Street, to implement new data management solutions, build data lakes and determine which service providers can accelerate their desired outcome – trusted data to make informed decisions.

Conclusion

In conclusion, investing in data integrity is not merely a technical endeavor; it’s a strategic move that can significantly enhance customer satisfaction. By breaking down data silos, achieving omnichannel excellence, and delivering personalized experiences, businesses can create a seamless and delightful customer journey. Moreover, in the age of big data, maintaining data integrity is the foundation for making informed decisions and staying competitive in a rapidly evolving business landscape.

In a world where data quality matters, those who prioritize it are best positioned to thrive and delight their customers.