Robert Doherty, Product Director of Nathean Technologies, discusses the role of analytics in CRM.
For too long many people viewed sales as an art, based on gut-feel and instinct, rather than a science. In the latter half of the 20th century, primarily led by sales experts in the US, the “mystery” was removed from sales and today most people believe that the key to successful sales performance is a well understood process that brings the sales person and their customer to a successful deal through a series of well-known stages. Most modern CRM solutions support this process driven sales effort but unfortunately for sales managers they do not provide the agile business tools that are required to accurately manage & monitor the sales effort.
When I consider the role of analytics in CRM today there are two quotes that instantly spring to mind. The first is from Peter Drucker, who is often referred to as the man who invented management. He said, “You can’t improve what you don’t measure”. The second appears in many variants but the one I like is, “Sales people deliver on what you inspect not what you expect”.
The failure of CRM solutions to allow us to measure our most important sales metrics so that we can improve sales efficiency and forecasting accuracy is the reason that Best-in-Class organisations are turning to third party analytic solutions in ever increasing numbers. A recent report from the Aberdeen Group entitled, “Better Sales Forecasting through Process and Technology”, proved that 81% of the best performing sales organisations utilise performance dashboards compared to 54% of other organisations. These organisations are also planning to increase their investment in sales analytics by, on average, 13.1% year-on-year so that they maintain their perch at the top of the sales tree.
Key CRM Analytic Challenges
In my opinion there are four key challenges that must be overcome in order to produce meaningful measures of sales activity from CRM systems.
The first challenge, and the one that is most common, is the quality of data that exists in the CRM system itself. Sales people by their very nature tend not to be inclined to spend time recording meaningful information about their leads and opportunities. They want to get to a deal and can often see CRM as a bureaucratic bump on the road to earning commission. Successful sales organisations recognise this personality trait and take action to overcome it. Regular CRM training is an essential part of this. Many leading companies seek to automate as much of the data input as is possible by linking to other systems, for example voice calls or email, or by introducing automatic triggers that move leads and opportunities through stages so that the sales reps data input is minimised. In my experience analytics can help here too by providing a set of exception reports and metrics that monitor data quality. This allows sales managers to quickly identify problem areas and to take remedial action when required.
The second issue that needs to be dealt with is the removal of the “human factor” in sales forecasting. Even when an organisation has a defined sales process with sales stages and associated deal closing probabilities, the sales rep can still overstate their monthly, quarterly or annual forecast through over-confidence or a lack of willingness to face the hard truth. The best performing businesses use analytics to identify this problem and to minimise its impact on forecasting accuracy. Past opportunities are used to predict how current leads will pan out. Facts such as age of opportunity, last activity or next planned activity can be used to more accurately predict the chance of closing in the forecasted timeframe.
Thirdly, I often find that organisations do not measure their “deal velocity”, which looks at the ideal progress of a lead through the various sales process stages and identifies where they are currently faltering and are therefore unlikely to end in a successful deal. Again, analytics can solve this problem by presenting clear metrics that identify exceptions to the sale manager, which he or she can then quickly investigate. Sales reps can then be re-trained or sales processes can be adjusted to produce a more efficient & better performing sales team.
Lastly, I firmly believe that CRM analytics should not be restricted to either the sales team or to the senior management in an organisation. Best-in-class organisations realise that sales forecasts have an impact not just on the organisation’s total revenue but have a knock-on effect in areas such as staff hires, supply chain, logistics and purchasing. These organisations ensure that stakeholders in all these areas have access to the right tools to enable them to plan for the future with confidence.
Selecting the Right Analytics Platform
In my opinion the key objective when selecting an analytics tool for CRM (and indeed for any Enterprise business intelligence tool) is that all stakeholders must be able to get the answer to their key questions in an acceptable amount of time. In today’s world that often means that information must be available in real-time. Indeed the Aberdeen Group report that amongst top performing companies, 50% provide real time sales forecasting analysis with 100% being able to pull a sales forecast in less than 2 hours. Contrast that with the worst performing organisations where 31% take more than 4 hours to generate a sales forecast.
If an organisation wishes to match the performance of their top ranked peers they must select an analytics platform that:
- Supports real-time analysis of their CRM system whether it is on-premise, hosted or in the cloud.
- Allows power users to build new rich datasets that can be used in a variety of agile ways by the various tools.
- Provides easy-to-use tools for users of all capabilities including:
- – Dashboards so that key metrics are presented visually and are easily understood. Exceptions are identified & highlighted and anomalies can be quickly investigated using drill-down functionality.
- – Analytics so that metrics can be easily created, represented visually, quickly added to dashboards and shared with colleagues.
- – An end-user query tool so that users can ask their own ad-hoc questions and can share insights
- Has a low Total Cost of Ownership (TCO) so that on-going training, maintenance & development costs are minimised and a low Total Cost of Change so that as the business evolves the platform can react quickly & economically.
- Connects to other business systems and combines data with CRM to increase the breadth of knowledge available. Some real world examples are introducing marketing data so that campaign to sales statistics can be generated, finance data so that actual sales can be compared to sales forecasts, Payroll & HR data so that cost of sales can be more accurately calculated.
The leading 20% of companies that implement CRM Analytics as described above report:
- A 90% customer retention rate versus 76% for the middle performing 50% and 41% for the worst performing 30%.
- A 13% year-on-year increase in sales quota achievement versus a 1.3% increase (middle 50% ) and a 5.2% decline (worst 20%).
- A 6.5% year-on-year reduction in average sales cycle versus 1 1.1% reduction (middle 30%) and a 4.7% increase (worst 20%).
For these companies total revenue increases 8.6% year-on-year, margin increases by 4.7% and lead conversion improves by 1.2%. In addition to these measurable figures and statistics, general confidence improves in the company and all departments can better plan for the future.
CRM Analysis Trends
The world of CRM Analysis is evolving all the time as more and more organisations see the value that can be unlocked in their sales data and the benefits that can then be accrued. Some of the trends that can be seen in the market include:
- The addition of social media data to the CRM mix. More and more organisations are using social media to spot opportunities and gauge public reaction to their products, their competitors and their industry. While the value of social media data is still a little unclear to many (see Facebook share price) we expect to see it play an ever more important role in the coming years.
- The move to mobile to continue. Everyone has seen the statistics relating to smart phone and Tablet adoption rates. Analytics are already available on these devices and we expect this trend towards analytics-on-the-go to gain more and more traction. With this in mind the impact of Microsoft’s new Surface device will be of interest in the short term.
- CRM Analytics in the Cloud. Many of the market leading CRM products are of course already cloud-based including Salesforce and SugarCRM. There are already cloud based analytic options for these solutions but currently they do not lend themselves to easily integrate with other data sources that may or may not also be cloud based including Finance, HR, Payroll & Marketing data. We see this integration as an essential part of CRM analysis and expect to see some new & very clever cloud-based solutions soon.
What are your thoughts on CRM analytics? Please leave your comments below.