Customer analytics allow marketers to dive deeper into their customers’ behavior across a multitude of data points to get a more accurate view of their customers. Through customer analytics, marketers can answer important questions such as ‘who are our best customers?’, ‘which channels work best?’, and ‘where can we intercept the customer journey to improve their experience and increase conversions?’.

Customer analytics have the potential to promote business profitability by surfacing insights which enable correct business decisions to be made, increasing customer revenue or reducing inefficiencies in the marketing, sales and customer service teams. Meaningful and accurate customer insights must be based on trustworthy, reliable customer data, yet most companies today are dealing with data that is incomplete, inconsistent, inaccurate, inaccessible or fragmented, resulting in business and marketing decisions being made that fail to yield the desired results.

In the best case scenario, a data science team or specific business users will spend precious time cleaning up the mess. In the worst case scenario, time is not spent cleaning the data and faulty data becomes the foundation for poor decisions. It’s not a pleasant choice!

By the CDP Institute’s RealCDP definition, a true Customer Data Platform must be able to ingest data from any source, capture the full detail of that data and retain it indefinitely (subject to privacy constraints), create a unified profile of an identified individual (that is, a Single Customer View or SCV), and share that profile with any system that needs it. This sounds like a marketer’s dream – but doesn’t guarantee that marketers will be able to access and leverage that data to gain insights, enrich the customer profile, and meet regulatory obligations. For that, an added user interface is needed.

Poor quality data is the result of numerous errors that can progressively ruin the success of your marketing campaigns. In fact, according to IDG, poor data quality is one of the modern marketer’s biggest concerns, with 66% of those polled declaring data quality and accuracy as a “top priority”. 

Inaccurate names, addresses and contact details, along with duplicate records and decayed information, will distort your view of a customer, resulting in poor campaign results and inaccurate insights. Worse still, it creates a bad experience for your customers whereby they either miss out on a specific offer, are targeted wrongly or receive the same message multiple times.

Data analytics is an essential function of any marketing department, but sadly underutilized for a variety of reasons. Firstly, the analysis and preparation of data is rarely the reason that marketers get into the profession. Often a skill that comes with IT and technical-related jobs, data crunching is not always a task that is as glamorous as working on creatives, the brand positioning or briefing in the latest advertisement.

Customer insight is all about analyzing your customer data to better understand who your customers are, and what they want from your brand, to help you to make better decisions about how, when and what to sell them.

These insights allow marketers to improve their customer experiences, optimize their campaign results and increase profitability. Despite this, many marketers aren't using customer insights to their full potential, and continue to waste budgets due to misplaced ads.

By using their customer insights to make data-driven decisions, they can achieve the same results with less money, by ensuring that their campaigns are reaching the right people, on the right channel, at the right time.