Sales professionals have seen their roles change massively over the past few years. From being the principal point of contact, to now as one of many sources of information, sales representatives are at a critical juncture of their careers. They need to stand out from the crowd, establish credibility and have a different set of tactics to win. Research by CEB shows that 57% of a purchase decision takes place before any contact with sales, while Sirius Decisions believes this number is even high, at 67%. As customers are more informed about the wider industry trends and their options, what can sales professionals do to improve their chances of success?
Even though today’s buyers are in more control and further ahead of the curve in the buying cycle, there are ways for sales to get involved in the purchase process early.
For one, sales professionals with industry expertise can offer more. They not only have information about their own products, but also can now provide insight and context on how customers should tackle problems. In some instances, this may mean disqualifying early and stepping out of the sale process where the chances of success are not high, or where there is not a good fit for products. This “consultative” sales strategy is valuable for customers, helping them see the sales process to their advantage. It also creates a competitive edge for the sales rep by helping them offer “business value” when other vendors, with self-interest agendas, are only skilled in pushing their products.
While this level of knowledge relies on the qualitative side of sales skills, years of experience and expertise in a specific domain, there are other quantitative skills that can help sales succeed as well. The good news is that getting your hands on data does not require a long learning curve.
Let’s take a look at how sales professionals can use data to make the most out of their opportunities and win.
The role of data in sales planning
Danish physicist and Nobel Prize winner Nils Bohr once stated, “Prediction is very difficult, especially if it is about the future.” For many sales leaders, the main use of data lies in the forecasting element of sales planning. While forecasting can give you a good idea about what will likely happen, you need to examine your forecast in a few different ways to ensure its accuracy. Applying historical conversion rates is a good first step, but history does not always repeat itself. For example, just because an opportunity is in stage 5, and you have historically closed 90% of your stage 5 opportunities in the same quarter, it does not mean that it is most likely going to happen this quarter too. What is your confidence level in that 90%? Does the account have all the characteristics of your most likely buyers? Do you have a way to assess the account against factors such as other industries, regions, numbers of decision makers, products requested, etc.?
Similar to forecasting, pipeline analysis should also be done at a granular level. Basic pipeline analysis can only help you measure your pipe volume and spot gaps. More advanced analysis helps you look at early indications, opportunity progression or where deals are stalled. For example, if the pipeline has increased by 10%, it’s important to look at how that increase was created. Was it because deals were moved from previous quarters to this quarter? Or that net new deals were created as a result of new marketing programmes? Or that the sale reps are planning to upsell into existing accounts? To answer these kinds of questions, sales leaders need to look at pipeline velocity by sales rep as well as velocity in context of marketing campaigns.
Another popular use of data in sales is analysing past sales success as a guide to future actions. For example, knowing places where you have proven success will help you gain credibility within the organisation to increase sales spend around key account management tactics, channel strategy, lead qualification and joint sales and marketing activities.
Where the data comes from
In order to use data to predict revenue or know which sales opportunities you need to focus on, you need more than just the CRM application. You need information from services, marketing and operations.
As an example, a sales manager that is selling into the large enterprise space needs to look at previous success in selling into similar companies, the length of the sales cycle, the size of the deals, the number of decision makers in the buying cycle and the products of interest. This information lies in the company’s ERP and legacy data warehouse systems.
In addition, by bringing together information from the company’s web clickstreams, marketing automation, social channels and operations applications, the rep can see how their targeted account is engaging with them. This analysis can also show if marketing has been in communication with the customer and get a good pulse on the customer’s response and interest levels. On the operations side, the analysis makes it possible to see how quickly customers pay once they are acquired.
By linking data together and analysing the whole “lead to revenue” process, the right targets and buyers become clear. This kind of analysis can also take a broader role, showing other segments with potential growth, or on the flip side, identifying the type of customers that have longer buying cycles and pose a potential risk to cash flow.
The ability to combine data from multiple applications and answer new questions means thinking about topics that are beyond the traditional purview of sales. This provides sales leadership with opportunities to lead the company’s strategic approach.
What if your data is not 100% clean?
Unlike popular belief, dirty data can be the impetus to get an analytics project moving. Many find that exposing dirty data to executives is much more powerful than cleaning the data prior to analytics. Analytics actually exposes data and process issues.
In addition, knowing that you have a way to keep a snapshot of all prior pipeline stages, incentivises members of the sales team to enter correct information into the CRM system of record, keep information up to date and avoid pushing sales close dates back and forth which creates wrong expectations.
Using data for strategy and tactical support
Data has become a strategic weapon for many companies. However, there is no “one size fits all” approach to data that companies can take. Each company runs its sales and operations teams in different ways. A company that provides one-off products is different from a company that offers services or a company that is built on a recurring revenue model. For each of these kinds of business, use of data for sales ranges from tactical to strategic.
On the tactical side, sales professionals can use analytics to answer pricing questions: What price is likely to succeed in a certain region or for a certain company size? Having data and some benchmarks to work against helps sales professionals know their buyer’s willingness to pay and avoid leaving money on the table.
Another tactical use of data is around opportunity or deal scoring. With hundreds of calls a day, knowing which deals are worth chasing and which ones are better to let mature can provide tremendous productivity gains for a sales organisation.
Using data, sales professionals can get a more prescriptive guidance on how to improve their chances of success. This can include suggestions for approaching specific sets of customers with bundles or offers that would fit better with their needs.
Strategic sales planning gives insights to managers to determine their pipe strength, quota coverage and lead flow. This level of strategic approach helps managers put in place additional training, coaching, lead generation programs and performance incentive plans.
Another example of strategic planning is to use data to show where and what regions have higher value opportunities that are underserved and need attention. This analysis can influence hiring and re-structuring decisions.
In the future, as sales shifts to take more of a strategic approach around customer understanding, data will become increasingly more important. Identifying the next best steps for engaging with buyers, positioning the right product or service, setting the right price and realising customer’s propensity to buy is among a few things that data-driven sales organisations can easily achieve. In addition, at a macro level, sales management can create a more effective sales organisation that is aligned with the market opportunities and has a constant flow of leads and pipeline to build a profitable revenue flow.
By Farnaz Erfan, Director of Product Strategy, Birst