Is ‘dirty data’ damaging your business?
The last decade has witnessed a rush on data. Every click, call, text, transaction — consumers provide vast amounts of data that could be used to create lasting value for brands and their customers. But too often, this wealth of opportunity goes wasted as untapped potential.
Most of this data is 'dirty' — out-of-date, incomplete, incorrect or duplicated. It's coming in fragmented from a variety of sources and multiple clouds, and it's constantly changing, making it increasingly difficult to discover, manage and derive intelligence. This means many companies are missing out on amazing opportunities before they're even aware of them.
According to a recent study from Validity, 44% of respondents estimated their company loses more than 10% of their annual revenue due to poor quality CRM data. Even more, the companies surveyed reported they lose customers, blow new business deals and delay revenue-driving initiatives like marketing and brand awareness campaigns thanks to subpar data.
However, the real reason isn't necessarily the 'dirty data'. The truth is, customer data will always be messy. The idea that it can be 'cleaned up' is a costly distraction. While the organisation is busy trying to tidy the data, processes remain inefficient, employees continue having a heavier lift, and customer experience remains clunky.
So, instead of trying to 'clean' the data, organisations need the right technology. They need technology that takes a flexible approach to gathering and matching data and can account for its ever-changing nature – allowing organisations to (finally) put their data to work.
The economic impact of 'wrangling' messy data
Customer data is always coming from different sources and in different formats. And it's constantly evolving as people move through life. Therefore, it's natural for data to be disorderly. Brands that don't embrace that fact suffer needlessly. The act of constantly trying to 'clean' their data takes the focus off the things that truly matter – teamwork, productivity, employee satisfaction, customer service and the bottom line, to name a few.
When brands and organisations stop fighting against 'messy data' and start working with it, great things begin to happen for the business, employees and customers.
The true cost of not getting identity resolution right
By wrangling 'messy data', brands continue to miss the mark. They end up treating their customers like strangers – and it's costing them big. Consider this: When you have multiple versions of the same people in your database, you end up spending on duplicate marketing messages. At first thought, it may not seem like a big deal. However, on closer inspection, you'll see that if you spend $10 million a year on targeted marketing but have a 25% duplication rate in your customer data, which is not uncommon, then you're wasting $2.5 million – that's a very big deal.
On top of being a big blow to the budget, customer service also suffers. Without a clear, unified view of your customer; you're building marketing campaigns and providing service based on incomplete and possibly inaccurate information. If you can't see your customers as complete people, it's hard to make them feel understood.
Even more, personalisation suffers. Part of personalisation is delivering your customers what they want when they need it, which means you have to know and understand those preferences. Duplicate data only muddies the waters. Nowadays, people expect good personalisation. And if brands get it wrong, they'll quickly move on to the brand that can get it right.
Identity resolution for the win
Identity (ID) resolution is the process of connecting and matching different data points across multiple devices and channels to form a unified view of a single customer. It allows brands to connect the dots between their 'messy data' to form a complete picture of an actual person. ID resolution holds the key to treating your customers like the unique individuals they are, setting the stage for happy, repeat customers and no wasted money on duplicate marketing.
That's why getting ID resolution right is the cornerstone of any brand's success. When all departments across the company have the same access to customer information in real time, customers are guaranteed a seamless journey at every touchpoint – whether that's online, in-store or with customer service.
When it comes to the impending deprecation of third-party cookies, ID resolution emerges as a valuable resource. By building a hearty, privacy-compliant, first-party data set, ID resolution provides a buffer against increasingly strict privacy policies that limit the use of third-party data. And even more, it helps improve marketing performance and ROI, too, with smart segmentation, which helps brands cut down on redundancies.
However, ID resolution can be a tough nut for brands to crack. But with the right technology to provide a strong customer ID foundation, brands can build the most accurate and comprehensive view of their customers and grow their business.
How customer data powers today's enterprises
Marketing: Grow the business by winning new customers and keeping them. Orchestrate cross-channel journeys, enrol customers in loyalty programs and unlock marketing that delights customers with real-time experiences.
IT: Give other teams direct access to data for exploration in a single, merged Customer 360 database. Integrate new data sources and protect customer privacy.
C-Suite: Get a clear view of customer metrics that let you see how your business is really doing, like how many customers you have and how valuable they are to your brand.
Digital: Strategic marketing to personalise digital experience across web and mobile apps. Coordinate consistent touchpoints and get a real understanding of ROI.
Finance: Forecast based on historical and predictive customer lifetime value. Use customer metrics for M&A analysis.
Customer Service: Give customers more personalised service based on real-time access to their full history of interactions with the brand, including special experiences for your best customers.
Products & Experiences: Plan and refine products and services based on how customers engage with your brand, anticipating needs and friction points.
Analytics: Build business intelligence dashboards, measure performance, run models and predictive analytics, strategise segmentation and find customer insights. Make strategic recommendations to help the business grow.
