Selling In a Downturn Requires Doing More with Data

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According to the Chief Economists Outlook published by the World Economic Forum in September 2022, 7 out of 10 economists now consider a global recession at least somewhat likely. The sales organization has a front seat view to the impacts of recession as sales personnel hear their customers cite budget cuts, postpone purchases, and possibly look for less expensive alternatives.

Not all sales organizations seem to be well prepared for a recession. A Bain survey of sales operations executives, in partnership with Research Now SSI, found that only 43 percent of sales organizations develop plans for a recession well in advance. Although businesses have been through recessions before, it has been more than a decade since the great recession. The difference this time is the plethora of data, tools, and insights that are now at the disposal of sales organizations.

While “do more with less” becomes the mantra for most sales organizations during an economic slump, sales organizations must instead “do more with data.” Leveraging data to uncover insights such as deals to prioritize, buyers that need more engagement, and sellers that need coaching and assistance are among several of the ways to utilize data as a strategic asset to bolster sales.

Here are few ways in which you can “do more with data” in your sales organization during a downturn:

Reassess Accounts and Focus on the Right Opportunities

Per McKinsey, rather than reviewing and reallocating coverage once a year as is typical of many B2Bs, outperformers are 50 percent more likely than slow growers to adjust their accounts monthly. This means that sales leaders with outperformers revisit account priorities more often and realign coverage and resources. Such assessments become even more necessary during a downturn as customers are forced to adapt and act more quickly. Sales leaders should base their decisions on focus accounts using data on customer investments, their priorities and how customers relate to the company’s solutions. Data can also be leveraged to measure effectiveness of sales activities across multiple customer contacts within the account - who is being engaged and by whom, how active are those being engaged, what content are they consuming, and what actions they are taking. Such insights become valuable inputs to account-based sales and marketing plans.

While it is necessary to be optimistic and important to consider that every single lead or opportunity matters during a recession, it is not pragmatic to pursue every opportunity. To enable sellers to focus on their most probable opportunities, sales organizations should be equipped with information on the true value of the opportunities within the account, i.e., untapped customer potential and customer profitability. This will require sales organizations to partner across departments to combine data such as share of wallet, solution alignment to customer goals, financial case for change, competition, and stakeholder analysis and profitability by product or service to prioritize opportunities. In this way, sellers can make an informed decision regarding the attention every opportunity gets. It also helps them to identify opportunities that they should direct to less expensive channels (e.g., digital sales, low-or-no touch buying experiences) or even walk away from. (e.g., less profitable deals).

Such an approach to prioritizing accounts and opportunities increases the quality of the pipeline, optimizes seller time, and increases the likelihood of sellers attaining their quota.

Maximize Seller Performance with Personalized Training and Coaching

According to McKinsey, top sales organizations tailor learning journeys for their sales teams down to the individual. Most sales organizations have learning management solutions and measure engagement (enrolment, progression, completion, time spent etc.) and experience (course rating, platform, ease of use etc.), but fall short in measuring effect (knowledge retention, behavior change and impact on the business).

Data and machine learning are invaluable when it comes to measuring effect and answering questions on how much sales training can improve skills, and which skills when improved offer the highest return on investment. Machine learning can help mine behavioral data from sales rep interactions, find patterns and generate insights about the behaviors that contribute to wins. Such findings, when combined with data on reps’ strengths, learning styles, skill gaps, and actual performance metrics (not just traditional sales metrics such as quota attainment, but also customer focused metrics such as customer retention and customer satisfaction) can provide a closed loop analysis for sales training.

Such a holistic approach also helps sales leaders identify who needs reinforcements and the kind of reinforcements (e.g., coaching) they need to drive top line growth.

Improve Seller Productivity

LinkedIn’s Global State of Sales 2022 Report shows that sales professionals spend less than one-third of their time (30 percent) actually selling, with more time given to administrative and other non-selling duties. Selling time is valuable, and periods of uncertainty warrant that sellers spend more time with their customers and prospects. Most sales organizations have a sales tech stack with lots of capabilities. However, sales tools are not necessarily well integrated into sales workflows or with other tools (sellers repeatedly enter the same information in different systems) which limits what they can do improve sales productivity and seller experience.

Sales automation helps improve productivity by automating repetitive and mundane sales tasks. Another way to improve productivity is to incorporate analytics into the sales methodology and with the activities that sellers undertake regularly. Let’s take the example of sales forecasting. HubSpot found that while salespeople spend 2.5 hours on sales forecasting each week, their predictions are typically less than 75 percent accurate. By aggregating and collating a variety of data points from CRM and sales order systems and using machine learning, sales organizations can benefit from a predictive forward-looking forecast with higher accuracy. Sales can also identify drivers and actions that influence buying and model different scenarios. Equipped with such insights, sellers can determine which deals to prioritize, how to move forward, and plan customer interactions.

This is one of many ways in which analytics can help reimagine sales processes and simplify sellers' work, giving them back more time so that they can focus on what truly matters - spending time with their prospects and customers and building their pipelines.

It is hard to predict the exact timing and the impact of a recession. However, we can say with certainty that sales organizations that embrace the possibility of recession, prepare, and invest for the future by becoming data-driven have better chances of not only surviving the downturn but also emerging stronger and thriving.

Sales organizations that embrace the possibility of recession, prepare, and invest in becoming data-driven can not only survive but also emerge stronger and thriving.

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