Nasty numbers: Why is sales analytics becoming a 'must-have'?
In 1935, AGA was struggling to sell its latest model of kitchen cooker to British homeowners, and so executives enlisted the help of a “rising star” in the Swedish firm’s sales team: David Ogilvy.
His solution was to produce a manual that AGA’s salespeople could adhere to – a step by step instruction booklet that gave those doing door-to-door selling everything they needed to know in order to turn all their prospects into sales. It was an instant success.
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Ogilvy eventually moved to the US to cut his teeth in advertising, and quickly became one of the industry’s leading figures – the “King of Madison Avenue”. But the manual remained a blueprint for sales people across the globe for many years to come. Even as recently as the mid-1980s, Fortune magazine was still calling it “the best sales manual ever written”.
Fast-forward to present day, however, and leafing through the pages of Ogilvy’s sales bible reveals a discipline very much of a bygone era:
“There are certain universal rules. Dress quietly and shave well…do not wear a bowler hat…study the best time of day for calling; between twelve and two pm you will not be welcome, whereas a call at an unorthodox time of day - after supper in the summer for instance - will often succeed……pretend to be vastly interested in any subject the prospects shows an interest in…the more prospects you talk to, the more sales you expose yourself to, the more orders you will get.”
Today, the discipline of sales may adhere to some of the same underlying principles, but the idea of a salesperson being able to simply dress appropriately and have a shave in order to win more business seems about as likely as them winning the lottery and getting struck by lightning in the same week.
Flanked by the perfect storm of rapid technological change, shifts in consumer behaviour, bloated marketplaces and new channels of communication, the average salesperson is very different to the one that once invited himself round to houses after supper in order to sell the latest kitchenware.
Andris A. Zoltners sums things up in the book, The Power of Sales Analytics: “As sales leaders ponder the challenges of structuring, sizing, deploying, hiring, developing, motivating, informing, and controlling their sales organisations, they are working with a new generation of technology-savvy workers and an explosion of data and technology that has several components:
- “Escalating volumes of information on customers, sales transactions, market potential, competitors, sales activity, and sales people.
- Social networks such as Facebook, LinkedIn, and Twitter.
- More powerful and fast-changing computer, storage, and mobile communication technologies.
- Advanced models and analytics tools.”
The new generation of salesperson is understandably more technologically astute than those in the 1930s, but perhaps the biggest shift in thinking has been caused by how much the sales cycle has changed in the last 10-20 years.
“The way people are buying today has radically changed in the last decade,” says Jonathan Woodward, UK business lead for BI and analytics at Microsoft. “Organisations and consumers are far more educated in their buying position and spend a significant amount of time researching and reviewing their options before even thinking of engaging a salesperson.
“This means that in some instances a salesperson will never be involved in the sales cycle when a customer buys direct, online or via an another channel. When a salesperson is engaged they will be far further down the sales cycle and engaging with very well informed customer.
“So, two main areas have changed in this new world: marketing has moved from just an awareness engine to being the customer awareness, nurture and advocacy engine that supports sales more than ever before. And sales has moved to engage far more analytically, to ensure that the deals they engage with are the ones that have the highest chance of closing and winning, leveraging all the insight that is collected before and during their engagement.”
The slow burning effect
Such a change in characteristics has led to analytics slowly becoming a cardinal tool for sales teams, especially those in mid-to-large size businesses.
While the analysis side is by no means a new concept, (even back in the 1970s, Xerox’s head of sales operations, J. Patrick Kelly was pioneering sales analytics, describing the process as “all the nasty number things that you don’t want to do but need to do to make a great sales force”), the technology evolved, the datasets exploded, and so the analysis of sales performance increased and sales leaders were able to use tools like Microsoft Excel and statistical software to manage their team’s pipeline effectively.
Yet up until recent years, the data being gleaned in the process of the sales cycle remained, for many teams, elusively complex to understand – continuing to represent the “nasty number things” that J. Patrick Kelly so aptly described.
“Why has it taken nearly 40 years for sales analytics to become widely accepted as an essential sales management tool?” asks Neil Rackham, author of SPIN Selling, in his foreword for The Power of Sales Analytics.
“A primary reason is that in the early days, nobody knew what data to analyse. My own research in the 1970s provides a good example of the problem. We wanted to measure the skills most linked to sales success. Our purpose was to analyse the behaviours used by successful salespeople during sales calls and to use that information to train and coach the rest of the sales force. We needed to decide which behaviours to analyse.
“Hundreds of observable things happen in the average B2B call. We ended up measuring more than a hundred different possible behaviours before we found the half dozen trainable behaviours that we were looking for. Until we had built a valid success model, we didn’t know what data we should be collecting for analysis. Initially, this work was just as wasteful and expensive as the seat-of-the-pants approach that we wanted to replace.”
However, in time, businesses have come to implement more sophisticated data management and storage systems, and this has helped bring sense to the use of data across every organisational department. CRM systems have evolved, and while still viewed upon with an air of suspicion in some sales teams, have burgeoned to become the go-to platform for data analytics to take form. So much so that Rackham calls analytics the “newest sales ‘must-have’: a contender for the next big thing to follow after mobile CRM”.
The business benefits of sales analytics
According to the 2015 State of Sales report, there’s a 58% increase in planned sales analytics use from 2015 to 2016.
“Analytics are the key that enables the VP of sales, sales operations and front-end sales organisations to move from a culture based only on gut feeling and perception-based decision making to one based on factual data supporting tactical and strategic decision making,” say Gartner analysts Praveen Sengar and Bhavish Sood, in their Five Best Practices to Strengthen Your Sales Analytics Initiative report.
Sales analytics, when not used in isolation, are said to have the power to transform sales performance. According to Sirius Decisions, sales analytics “enable more effective, fact-based decision making”, and sales leaders should “leverage analytics to complement their judgment and experience”. These analytics give sales teams more of an understanding of their pipeline and funnel, and a better idea of what’s going on in certain stages: when deals will close, how long they’ll take, and more.
Jonathan Woodward perhaps puts it best when he says, “the benefits of having insight into win/loss prediction, sales rep performance, pipeline prediction, year-over-year comparison, real time opportunity scoring allows sales rep to address the single biggest issue: time. Sales Analytics = Sales Productivity = Increased Revenue.”
Indeed, the 2015 State of Sales report states that high-performing sales teams are three times more likely to be using sales analytics to drive sales than those under-performing teams.
When used within a team that full embraces the processes, sales analytics tools are able to take data and answer any of the following questions for sales leaders:
- Which deals are most likely to close?
- Which sales rep has the best chance of closing this opportunity?
- What is my predicted close rate on my pipeline?
- Why do I win /why do I lose deals?
- What is the next best action for this opportunity?
However, the challenge of creating a joined up, well-oiled sales analytics function is one that very few businesses can say, with certainty, they have achieved.
Doug Winter, the founder and CEO of Seismic, says there are three core issues with a sales department that mean analytics deployments often ‘fail’:
1. Analytics are not measuring the right things
“Companies will track how long sales cycles took from start to close, the number of calls and emails that turned into meetings, and more. But these are not measurements of how effective a sales force is. In order to track the success of sales analytics, companies need to incorporate measurements of sales effectiveness.”
2. The reasons for using analytics are misaligned throughout the organisation
“If the significance of sales analytics reports for each team and their meaning for the bigger organisation is not conveyed, it’s difficult to make any changes in behaviour or practices. If the entire organisation is not working towards improvement after analytics reports are shared and discussed, each month will be the same story and you’ll find yourself taking one step forward and two back after each meeting.”
3. Analytics are only getting companies so far
“Sales analytics are often expected to solve problems and be the reasoning behind making certain organisational decisions. But the analytics commonly tracked by most companies don’t get far enough down the funnel to fuel these decisions—the funnel remains in black and white. Being able to track the how and why, however, fills the funnel with colour and allows for better ways to improve sales processes and practices.”
And Jonathan Woodward adds that Winter’s second point, about the use of analytics being misaligned through an organisation, is potentially the most pertinent, as it often boils down to data simply not being given enough gravitas as a fundamental part of the business’s culture.
“A data-driven culture has been proved to enable your organisation to outperform your peers and unlock what IDC call the ‘data dividend’, unlocking additional revenue to the tune of $1.7 Trillion over a 4 year period worldwide.
“By acquiring the right data, applying analytics, putting it into the hands of the employee and doing this at speed significantly make a difference to the efficiency and financial performance of an organisation. By moving the organisation towards a data culture, whereby decisions are taken based on data, we allow ourselves to increase our productivity significantly.”
And one final, but no means diminished challenge sales leaders must overcome if they are to successfully integrate analytics is the need to get their sales team on board, because as with the early days of CRM, many salespeople often see the suggestion of tracking and analysing their performance as a means for leaders to keep tabs on them.
“In this respect,” Woodward adds, “sales leaders need to really drive home how analytics can improve their productivity.
“Time is probably the single most valuable commodity to salespeople. Being highly productive and focussed on the right deals as a seller is the difference between mediocre and typically stellar sales performance.”
And it is this hurdle and the best practices that associate with it, which MyCustomer.com aims to shed further light on in the coming weeks, as part of our ongoing guide to sales analytics.
Chris is Editor of MyCustomer. He is a practiced editor, having worked as a copywriter for creative agency, Stranger Collective from 2009 to 2011 and subsequently as a journalist covering technology, marketing and customer service from 2011-2014 as editor of Business Cloud News. He joined MyCustomer in 2014.