24 March 2021
AI and automation will be a staple of the B2B sales processs according to Forrester. Sales Enablement is booming in the US,…
1 November 2017
The 2016 Sales Performance Optimization Study by CSO Insights found that only 57.1% of B2B sales reps made quota last year. You might think that number is understated, but the rate was only 58.1% in 2014 and 58.2% in 2015. What’s more, B2B sales teams only achieved 82.7% of plan commitment last year. As sales professionals, we seem to have trouble reaching our goals.
When asked how they would turn things around in 2016, 58.4% set as a top goal, “capturing new accounts” and 40.2% said “improve sales effectiveness.” Both of these goals are supported by sales intelligence services which assist with lead qualification, account planning, messaging, and selling deeper into organizations.
The next three most cited objectives: “optimise lead generation” (39.3%), “increase existing account penetration (30.0%), and “improve customer loyalty/satisfaction” (21.9%) are also addressed via the implementation of a sales intelligence solution.
Put simply, the ROI is calculated as
More complex calculations build in a discount factor (interest rate) as costs are often front-end loaded with the benefits accruing later on. Fortunately, with cloud-based information solutions, the front-end costs are low and sales reps can begin using the information service almost immediately. While there is some initial investment in training and customisation, the cost structure is fairly flat and benefits are timed with costs, allowing us to skip discounting.
To calculate the ROI, you will need an estimate of the fully loaded cost of the average sales rep. This includes salary, commissions, benefits, wage taxes, annual expenses (e.g. travel, computer, office space), etc. You will also need to convert this to an hourly rate by taking the fully loaded rate and dividing by the number of hours per year the sales reps work. Thus:
Let’s begin by looking at the costs of sales intelligence services from the sales side:
Now let’s look at the benefits. These can be broken down into soft and hard benefits. Hard benefits are measurable and included in the model. Soft benefits are often intangibles that result in better performance but which are difficult to measure directly. In my last blog, I discussed both efficiency and efficacy benefits. It is the efficiency benefits which generally can be modelled and the efficacy (selling more effectively) which only show up in the final results.
On the hard benefits side, improving the efficiency of sales reps is necessary. CSO Insights found that only one-third of sales rep time is spent actively selling. Thus, simply reducing busywork by one hour per day by eliminating account, contact, and lead data entry; streamlining account prep; automating account awareness; reducing time spent on lead qualification, and facilitating prospecting (e.g. finding additional targeted contacts at accounts) results in significant sales leverage. I have conservatively placed the gain as one hour per day.
Over a year, the resulting efficiency gain is 46 * 5 * R or 230R per rep
Thus, a back of the envelope ROI for just the sales team puts the ROI at
You are welcome to adjust this model, but what is clear is that a modest decrease in busywork can result in a high ROI without making assumptions about efficacy improvements.
This model focused only on the sales department, but with ABM and increased calls for sales and marketing alignment, sales intelligence services have extended their capabilities into the marketing department. Brevity prevented me from providing a basic model for the marketing department, but you can build one in a similar manner. Just note that your cost structure is tied to the volume of data in your marketing automation platform and the frequency of updates. It also is tied to the number of new leads entering your MAP which are enriched. All of these can be calculated.
On the benefits side, there is a reduction in spend due to marketing costs associated with bad leads in your MAP (e.g. the company went out of business, the contact left the firm), lowered webform abandonment rates due to reducing the number of fields, and higher conversion rates due to improved prospecting, targeting, and messaging.
What is clear is that with sales reps so pressed for time to engage in direct sales activities, a small improvement in sales efficiency can justify investments in sales intelligence tools even without modelling for soft benefits.