This is a reprint from a posting in Eloqua's blog.
Editor’s Note: Today’s post comes courtesy of Frank Donny, founder and CEO of Marseli, a marketing and sales analytics and performance software company. Donny is responsible for the firm’s capabilities, software vision, and services.
According to a recent article from InformationWeek, “Vague Goals Seed Big Data Failures”, a sure way to fail a Big Data project is not having extremely focused goals. Fifty five percent (55%) of all big data projects fail before they are completed, according to the report, due to a lack of focused data. Additionally, having a focused set of KPI goals for a sales team is just as important as having the right data. Making this mistake could lead to disastrous repercussions to the overall performance of your company.
First, you need to focus on your business use case. Develop a set of 5-6 KPIs that you intend to track and report on a regular basis. The next step is to look for a sales analytics software application that will expose the results in a simple, efficient and affordable manner. The technology should be secondary to your use case.
Second, provide data access to everyone. This includes sales reps, managers, operations, marketing and anyone who will have any impact on revenue performance. This data access needs to be at the level of the sales rep, providing insights into their behaviors. Do not separate the analytics and the ability to drill into the data from the people who need it the most. These people are often your subject matter experts and are the people who will ultimately act on the data.
Third, make sure you can get to the “why” in your analytics. Most reporting tools do a fine job at pointing to “where” there is a problem, but you also need functionality to support the “why.” This third recommendation is key, because analytics are nearly worthless without the ability to answer “why?” The right strategies will enable your teams to use historical analysis to predict future performance.
Fourth, the data has to be linked to knowledge. It has to be actionable. By combining insights with knowledge (“how” to solve the problem) you have now provided your end users with a full roadmap to improve performance. A quick example: if a sales rep is not following your sales process and you have a report that shows the impact that this is having on their ability to sell, then you can provide knowledge along with the data (the facts) that will give them direction on how to improve.
The bottom line is that the data is only as good as what you do with it. Merely providing historical analysis at the management level will not help you to improve your performance. Improvement happens at the foundation level – your sales managers and their associated reps. By exposing the people at that level to the information and the knowledge, you will see a noticeable improvement in your performance and you will not fail your sales analytics project.