Businesses have access to customer data from numerous sources including their website usage stats, social media, emails, point of sale and call centres.
Unfortunately, the data being collected isn’t always of good quality. A survey by the Royal Mail’s Data Services found that poor quality customer contact data could be costing organisations in the UK as much as 6% in annual revenue.
Since 2014, the Royal Mail’s annual survey of UK marketing, data and analytics professionals has uncovered the same issues – namely incomplete, out of date or duplicate data. This is despite the fact that the survey’s respondents cited good quality data as having the greatest positive impact on campaign response and conversion rates.
So, how can companies tackle these data quality issues? To begin with, they need to develop a process for validating the data they are capturing. Nearly 20% of those surveyed by The Royal Mail didn’t have a data validation process.
Once this is done, the data needs to be sorted and segmented before meaning can be extracted from it. Segmenting customer data is fundamental to helping marketers target customers effectively. You can segment customers based on demographic details but even better is using the granular data that’s now available to segment based on behaviour. That’s when you can truly begin to use more effective marketing strategies like sending personalised communications.
Every marketer also needs to follow ethical practices when collecting and using customer data.
Protecting their customers’ privacy should always be front of mind. This means keeping up with the latest data legislation. Marketers who are lagging behind in terms of data compliance could face a hefty penalty when the new General Data Protection Regulation comes into effect in May 2018.
One of the requirements of the legislation will be taking a two-step approach to customers opting into receiving communications. It won’t be enough for customers to sign up to emails via a form for instance, they also need to verify this in a follow-up email. It is wise to begin taking this approach now, so your marketing efforts aren’t hampered in future.
Numerous surveys have looked at customer attitudes towards data sharing and shown there is a fine line between being helpful and being creepy. Cross it and you’ll put your customers off. One recent survey from Payments UK found that while data sharing has become part of everyday life, customers are understandably still wary of it. As many as 67% said they view their spending habits as private. This clearly presents a challenge for marketers who may want to use such details to target customers better.
So how can you build customer trust? One of the core tenets of using customer data is making sure you use it to offer relevant and valuable information. This will help make your customers less wary about sharing their data. Being open and transparent about how you’ll use their data is also key to building customer trust.
The privacy by design approach sets out seven core principles which can help guide your data use.
But even with all this in place, your data is not much use unless you analyse it effectively. Data analysis is continually getting more sophisticated and carrying out predictive analytics is one of the most valuable approaches you can take.
This involves looking at past behaviour and using it to predict what might happen, so you can be proactive rather than reactive with your marketing. Predictive analytics is now possible with machine learning, so it is worth investing in the technology to use it, or else your competitors will reach your potential customers before you do.
Another issue with analysis is being able to do it fast enough. It really needs to be done in real time but this can be costly and time-consuming. Once more investing in technology holds the key to tackling this issue.
Then, of course, there is the common issue that many businesses still keep their data in silos in different departments. Your analysis will be much more valuable once you have aggregated your data to give a single customer view, so you can make connections you might otherwise miss.
Another barrier businesses still face is taking action based on the insights they get from data.
Making data-backed decisions is of huge value but for some organisations this requires a major cultural shift. In a business where people are used to making marketing decisions primarily based on experience, putting trust in data can feel risky.
Airbnb is tackling this issue by setting up their own data university to educate all their employees in the value of making data-driven decisions and give them the skills and tools to do so. Embedding data use into your working culture will help all areas of your business, not just marketing.
If the challenges detailed in this article sound familiar to you, then I recommend taking steps to start tackling them today. The role of data is only going to grow and failing to use it effectively now will only make your work harder in future.