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How to measure the ROI of sales analytics

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14th Sep 2015

No matter what industry you work in, being able to demonstrate that you have made a return on investment from your sales analytics project is a must.

On the one hand, the board will inevitably be keen to see that its money is being spent effectively. On the other, it is important to be able to tell whether your time and efforts have been worth it.

So to help you get there, here are some key considerations when measuring ROI for sales analytics implementations:

1. Where will money need to be invested?

An obvious area for investment is either on the technology required to implement an analytics system in-house or on a subscription to a software-as-a-service-based offering that can be accessed online.

Current options here include add-on tools from salesforce automation (SFA) application vendors such as Salesforce.com or from enterprise resource planning (ERP) system suppliers such as SAP.

But software is also available from generalist business intelligence providers such as IBM’s Cognos or Microsoft, which in the latter case enable organisations to build their own predictive models from scratch.

Further possibilities comprise software-as-a-service-based specialists such as Pros, which sell pre-built models and industry-specific applications that cover either one element of the sales process or come as suites handling three or four.

2. Common areas of underinvestment

Another thing to bear in mind in this context - and one that is often overlooked or underestimated - is the amount of time, effort, and therefore outlay, that is required to identify relevant data sources, which includes SFA and ERP systems, and then ensure that the data itself is clean, accurate and consistent.

Failure to do so could result in the answers to the questions you ask your analytics system simply not being reliable because any outputs will only be as good as the data you input.

A further and again all too frequently neglected area of expenditure is on education and training. Introducing new key performance indicators (KPIs) to the sales team without explaining what they mean, why they are necessary or how they will benefit all concerned is highly likely to lead to dissension. It is also likely to see staff try to find ways to bypass or even pervert the process, which isn’t good for anybody.

Moreover, introducing KPIs, perhaps for the first time, combined with the insights provided by sales analytics data, can also often reveal areas where sales reps- and their managers - require training for professional development purposes.

3. How can I best demonstrate ROI?

According to Vera Loftis, UK managing director of business consultancy, Bluewolf, where a lot of people go wrong in ROI terms, is in spending lots of money on expensive analytics tools, populating them with data and then sitting back to “wait for the magic to happen”.

But in order to get the most of such software, it is important to break the processes around using it down into several areas. The first is employing the sales insight data you have collected to understand why your customers are buying what they do and when - or not as the case may be - and develop a strategy around these findings in order to optimise sales.

For example, if it becomes obvious that, while your sales team is great at acquiring new clients, it is not so good at keeping them or cross- and up-selling to them, then it makes sense to devise a strategy around customer retention as a straightforward way to boost sales.

The next step is to come up with KPIs that ensure your reps focus on the key outcomes outlined in your sales strategy. “A lot of people get KPIs and performance metrics confused, which makes them difficult to track, and that’s when ROI conversations get convoluted,” warns Loftis.

While KPIs are linked to behaviour, performance metrics focus on things such as year-on-year revenues and performance against targets. If the two become “tangled up”, however, it can become difficult to understand if an individual process is working or whether it needs to be modified.

But says Loftis: “The value of these new analytics tools is they can pool data insights, KPIs and performance data to give a rounded view of what’s happening in semi-real time. So it’s no longer about working with reactive, static reports once a year.”

Instead it becomes possible to see what is working well and what isn’t on an ongoing basis.

“If you follow the process consistently, ROI should be obvious,” Loftis says. “So your insights inform your strategy, which is based on KPIs, and if your sales reps do what they should, you should achieve your goals. If not, you can use your analytics tools to re-evaluate.”

But to make it all work, she warns that sales strategies must have ROI calculations built into them from the outset. “That is, if we follow this strategy and the sales rep follows this behaviour, this is the result we can expect,” Loftis explains.

4. Common pitfalls when trying to demonstrate ROI

A common pitfall when looking at ROI is simply trying to make the scope of initial sales analytics projects too wide.

The ultimate aim should be to include data from other areas of the business such as marketing and customer service as they all contribute to the sales process. But the secret is to start small and “crawl, walk, run”, according to Mike Grigsby, vice president of analytics at Omnicom’s strategic communications agency, Target Base.

For example, specific sales niches that are often worth exploring initially in ROI terms include lead-scoring, exploring product mix recommendations and improving sales pipeline visibility.

“You don’t have to put a huge system out there a year from now and wait for a return,” Grigsby says. “It should be immediate. Start small with a single use case, use it for three months and it should pay for itself. If not, you can pull the plug.”

But this links into another frequent error – trying to demonstrate ROI too quickly. A key consideration here though is that, because organisational and process change takes time, any ROI is unlikely to materialise in the first month or so – and certainly not before the three to six month mark.

But as Loftis concludes: “When you’re looking at analytics, it’s very methodical and logical in some ways so it should actually be the easiest of all business areas to demonstrate ROI.”

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