There’s huge demand from firms for CRM-as-a-service, made affordable by cloud computing. Lured by the promise of unifying the enterprise in its mission to manage customers better than ever before, businesses mustn’t forget that good CRM demands good data. Especially in a world of Big Data, it’s important to remember that it’s data quality, not just data quantity that counts.
According to a study by Nucleus Research, 63 per cent of enterprises with more than 1,000 employees have adopted on-demand CRM technology, while according to Gartner, around 35 per cent of all CRM applications use software-as-a-service (SaaS), likely to extend to 50 per cent by 2020. There’s been an explosion, too, in related marketing automation and customer data analytics solutions among senior marketers.
The attraction of CRM, of course, is the promise of unifying an entire enterprise based on its ability to sell to, serve and retain customers better than before and to be able to gain clear visibility into customer spend trends, improve engagement, service and loyalty and maximise lifetime value. Another Nucleus Research survey suggests every dollar spent on CRM delivers a $5.60 return. If only things were that easy...
Data challenges mean half not satisfied
Reportedly, at least 25 per cent of most companies’ data is probably inaccurate. In fact, research by Aberdeen suggests that of what it calls best-in-class performers (the top 20 per cent of companies as judged by its 360-degree customer view performance criteria) only 48 per cent of firms are satisfied with their data quality, as are just 36 per cent of the rest. (In the Aberdeen survey, 32 per cent of best-in-class companies and 44 per cent of others went so far as to say that they were dissatisfied with their customer data quality).
Research by independent analyst firm Ovum suggests bad data is costing US business around $700 billion a year (translated proportionally into UK GDP and converted to sterling, that’s about £70 billion for the UK), or 30 per cent of the average company’s turnover.
While a recent Economist Intelligence Unit report commissioned by Capgemini found that 75 per cent of the business leaders they surveyed believe their organisations to be data-driven, that data has to be of high quality. It’s not just about volumes. How can you possibly expect your data-driven CRM investment to enhance company performance if you can’t trust the customer data in the first place?
Data Quality’s the key to CRM performance
Key performance indicators (KPIs) for CRM investments typically include growth, such as conversion rates, cross-sell/up-sell rates, customer spend and retention, as well as process improvements, such as heightened contact centre productivity, reductions in sales order errors, reduced marketing costs per sale and reduced sales cycle times (in B2B). The better the data, the greater the opportunity to succeed in these areas.
Iceland Frozen Foods defined a clear data quality strategy to improve the effectiveness of its loyalty programme to ensure it could build reliable views of its three million-plus customers. Iceland cites the value-add as being improved decision making, higher response rates, improved acquisition rates and improved loyalty.
Good customer data means reduced waste from poorly targeted and duplicate mailings and protecting customer relationships from the brand damage and opt-outs associated with “marketing fatigue” (where customers are over-burdened with often off-target messages). It also permits the identification of new customers for nurturing and loyal ones for special treatment.
One of the big challenges to ensuring data is of high quality for customer relationship processes is that it now enters organisations in ever increasing quantities. In this age of Big Data, firms are seeing data volumes grow at a rate averaging some 50 per cent a year - and double that in industries like media, medical and insurance.
Single customer, real-time view
Before this huge flood of multi-format, multi-source data can be woven into meaningful intelligence to drive customer relationships, it needs to be cleansed, then matched with other relevant data from inbound channels as well as existing legacy data.
Given the volume, velocity and variety at which data is arriving, the challenge is one of latency. How can an organisation cleanse and match the data, then update the single customer view (SCV) fast enough? How can it support interactions that are happening right now with the most up-to-date data? The Economist Intelligence Unit report suggests that there is a real need to overcome this challenge, exposing that 85 per cent of those surveyed stated that they were experiencing issues due to their inability to analyse and act on data in real-time, with 56 per cent saying organisational silos were the biggest barrier to Big Data-driven effective decision making.
Three steps to achieving CRM-compliant data
The key to ensuring good data for CRM and to winning buy-in from CRM stakeholders is to create a CRM data quality compliance process which aligns data quality and CRM KPIs. This means ensuring that the data entering corporate systems and processes meets required standards for cleanliness, relevance and timeliness. There are three main data compliance steps:
Proceed with care
Embrace the customer relationship opportunities presented by data, by Big Data and by the ease of access to on-demand CRM. But exercise caution and heed the CRM data quality lessons of the past.
For all the value data insight can bring, inaccurate data can frustrate and undermine even the best-willed customer relationship efforts. Proceed enlightened to the importance of data quality, align your data quality goals to your CRM goals and you’ll most certainly be among the half that succeed!