Over the last few years there has been a huge increase in the amount of information collected, through improved SAP CRM systems and new channels to market such as Social Media. But what's the point of collecting these vast quantities of data on your customers if you're not using it to drive more strategic decision making?
This information can hold the key to what attracts your customers in the first place and what keeps them loyal over time. So the importance of using this information in an innovative, timely and accurate way can't be underestimated.
What stops the data being used?
It seems obvious that it's essential for organisations to capture every piece of information they can about their customers and their transactions. However, what stops this information being used to drive decision making? Common reasons include:
- Senior decisions makers (CXO level) are not bought into decision-making based on the information. The business needs to have a clear strategy to make decisions based on data and analysis.
- Lack of clarity around what questions the business wants to ask, so there isn't the driver for getting started.
- Too much existing data, or the wrong type of data, to answer any hypotheses effectively; this is normally caused by the systems not being in place to cope with data volumes or data not being integrated at the right level or accuracy. 'The problem with the quality of your data' by Jan van Ansem is well worth a read.
- The methods of data analysis involved are often complex, require specialist skills and are often either hard to understand or require considerable investment in software, hardware and time. However the tools to achieve these tasks are become more mainstream as the major vendors, including SAP, build the capabilities into their offerings.
How can I make the most of customer data?
Over the last few years we've seen some great examples of how data can effectively drive decision making. Here are a few examples.
- We implemented a Basket Analysis solution for a leading retailer which has helped to accurately target promotions, unlock missed revenue opportunities, drive sales, reduce redundant stock and improve margins.
- We used SAP Real Time Offer Management (RTOM) (including dynamic customer modelling and scoring offer) to deliver a fully personalised customer experience, where previously only a generic one was possible or affordable. Jim Cook wrote a great blog on this - Is it technology that's holding us back or just our imaginations?
- Integrating social media and other unstructured internet data into your Business Intelligence architecture can be used to increase the effectiveness of Marketing spend, increase customer satisfaction and increase brand awareness. Check out Social Business Intelligence - Like by David Allison
Where do you start?
In my experience it's key to keep thing simple from the onset. A project will not be successful unless it has a few fundamental foundations in place. The best starting point is usually a business critical issue that has the right senior level sponsorship to address, e.g. shifts in demand or perceived changes in customer behaviour.
The right people in the business owning the issue and focusing on solving it will make it far easier to articulate the questions that need to be asked. Once you have the questions to ask you know what data you need to use. This gives some structure to the business issue at hand, boundaries to work with and most importantly, a clear idea of the potential value-add.
The next step is to determine a solution that can address the business requirements as well as cope with potential blockers such as data quality. If you understand the value to be gained however, you can quickly judge whether the cost of a project is likely to be money well spent and ensure everyone is focused on realising those benefits.
Good luck understanding your customers better.