The three key challenges to building a data-driven retailer

The three key challenges to building a data-driven retailer

By Jim Conning, Managing Director of Royal Mail Data Services

Retail is increasingly powered by data. Only by understanding what customers want and delivering the right products through a personalised experience will retailers successfully win business and retain consumer loyalty. 

Emphasising the importance of acquiring and retaining customers, churn rates are currently running at 19%, which means that nearly one in five shoppers defects every year. That is one of the key findings of research carried out by Royal Mail Data Services with UK brands. The study also highlighted three other key trends:

1             The GDPR is the top challenge

The forthcoming implementation of the General Data Protection Regulation (GDPR) is shining a spotlight on the data that organisations hold on their customers and prospects. Unsurprisingly, compliance with the GDPR was the number one concern for respondents, cited by 29% as their biggest worry. This number had more than doubled since the 2016 study, when 12% listed it as a concern.

Looking in more detail, the study asked companies how confident they were that their internally held and third-party customer data was GDPR compliant. The positive news is that 78% of all marketers were either “very” or “reasonably” confident that their internally held customer data complied with the new regulation – although worryingly, 11% were not confident, including 2% who didn’t know if they were compliant or not.

However, when it comes to third party data the levels of confidence drop dramatically. Just 43% of respondents were “very” or “reasonably” confident when it came to compliance, which demonstrates the difficulty of gathering evidence that the right permissions are in place when data has come from other sources.

2             Analytics and data underpin marketing success

Marketers now have more data on customers than ever before. So what needs to happen to improve the overall performance of their campaigns and programmes? When companies were asked where the gaps were that need filling, 24% pointed to analysing customer data as their biggest issue. This demonstrates a clear need for greater analytics skills and capabilities. 

Companies also need to deal with two other major challenges. 28% of all respondents said legacy systems were holding them back. These can be inflexible and difficult to use, and act as blocks on using data to effectively meet wider marketing challenges. They also struggle to embed data cultures within their businesses. 21% said that a better understanding across the organisation of the importance of good quality customer data would improve performance. This demonstrates a need to put data at the heart of the entire business, not just within the marketing department. 

When it comes to driving successful campaigns in terms of response and conversion rates, marketers agree it is all about data and how you use it. On a scale of one to five, the four top success factors reported were quality of contact data (4.6), segmentation and targeting (4.6), personalised content (4.4) and timing (4.3). In comparison, creative design scored just 4.0 out of 5. These top four factors all rely on good-quality data and analytics in some way, and marketers reported that they had all increased in importance dramatically since 2016. 

3             The need to solve data quality issues

Poor quality data was cited as their biggest challenge by 18% of marketers. But what factors impact quality? When asked to prioritise the different causes of poor quality data, marketers pinpointed basic errors as the main culprits, specifically out-of-date information and incomplete data. The research found that problems such as duplicate data, spelling mistakes and data in incorrect fields tended to rank lower when it came to data quality issues.

Validating data as it is collected is key to maintaining good quality data. Although this is becoming an increasingly automated process, both on websites (for which 46% of marketers said they automatically checked address data) and in internal systems (40% automatic checks), 19% of marketers said they didn’t validate website data, and 16% didn’t check data coming into internal systems at all. 

An additional 25% relied on manual address checks in internal systems. At a time when good quality customer data and operational efficiency are high on the marketing agenda, there is clearly a need for businesses to find new ways to automate the continuous cleansing and validation of customer data.

Marketers understand that data is a living entity that quickly becomes outdated. The overall picture is that more companies are focusing on more formal, regular data cleansing – 22% said they did this daily or continuously, and just 11% annually (down from 14% in 2016). However, one third still had no formal processes in place to clean customer contact data, although this had dropped from 37% in 2016. This means a sizeable minority are putting themselves at risk of data quality issues – and potential GDPR investigations over non-compliance. 

Poor quality data hits the bottomline. Even without GDPR fines (which can be up to 4% of global turnover), marketers estimated the average cost of poor-quality customer data at 6% of annual revenue, a similar figure to that from 2016. For major brands this is measured in millions of pounds – and even this may not be the complete picture. Poor quality data impedes overall marketing performance, impacts response rates and reduces conversion rates, making the overall cost potentially much higher. 

In a retail landscape powered by data, marketers and brands have the opportunity to drive greater revenues through better use of customer information. However, they also face new challenges. Only by overcoming these will they be able to improve marketing performance, deliver great customer experience and drive revenue, both now and in the future.  

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