Data-Driven Selling: 3 Common Mistakes (and How to Stay on Track)
Data-driven selling can be incredibly powerful for distributors. The right insights and information, packaged the right way, provided at the right time, and launched with proper training can be a game-changer when it comes to driving profitable sales growth. This approach:
- Aligns the entire company around key performance metrics.
- Reduces perpetual firefighting and leads to more proactive, more responsive sales intervention.
- Arms the salesforce with insights that differentiate their sales pitches and storytelling, giving your sales reps and their customers more confidence.
- Puts the salesforce in a far better negotiating position when it comes to challenging pricing dialogues that often lead to long, leaky margin erosion.
While the benefits of data-driven selling are clear, efforts to integrate data and analytics into the sales process typically fall short of expectations. We have identified the three most glaring mistakes that distributors (and their analytics teams) make when it comes to missing expectations, which essentially boil down to which analytics get created and how those analytics get consumed:
1) Mistaking “data” for “insights,” which results in introducing more “noise” into the sales process than actual benefits.
2) Failing to display insights the right way (poorly designed dashboards with insufficient drill-down capabilities).
3) Failing to integrate analytical insights into day-to-day workflows.
I’m going to walk you through these three common mistakes we often find when assessing distributors’ data-driven sales capabilities and rolling out world-class sales dashboards that drive results.
Mistake #1: Confusing data with insights
Solution: Cut through the noise: Less is more.
When we review sales dashboards, the most common deficiency we see is that distributors mistake quantity for quality in terms of what they share with sales. Most companies treat data like the proverbial “haystack” and hand it off to sales to find the needle. It’s common to see tables upon tables (think “spreadsheet” views) of unusable sales data misconstrued as sales “reports.” .
If developing “spreadsheet” views of raw data is the problem, what’s the solution?
Rather than inundating sales reps with raw data, it’s important to carefully curate and summarize insights in a “drill-down” sequence. Carefully construct dashboards that:
- Prioritize which customers they should focus on (either to mitigate risk or attack opportunities).
- Drill down into root causes of concerns with any selected customer.
- Quickly spot sales/profit opportunities for a given customer.
- Develop concrete, data-driven talking points when it comes to communicating insights to customers.
Ideally, try to distill performance into more visual (think “graphical”) summaries of two to three critical metrics at a time that can be shared with sales and used for further drill-down. The ultimate solution is customer stratification (the “silver bullet”) because it creates composite metrics on just two axes and then visually plots them:
1) A top-line/volume-driven score
2) A profitability/cost-to-serve score
Stratification effectively takes a double-digit column spreadsheet full of “noise” and turns it into two core metrics. If you don’t use stratification dashboards, we would still recommend graphically homing in on two to three metrics max to evaluate top-line growth (sales, product category penetration) and profitability performance (gross margin, average order size).
Mistake #2: Poor dashboard design and granularity of analysis
Solution: Integrate benchmarking and deeper drill-down capabilities.
Key principle #1: Benchmark, benchmark, benchmark
We talked about the importance of narrowing down what you show sales, but that’s not enough. You can still fall into the trap of providing numbers without context. Ideally, every dashboard should answer the question, “Is this good or bad?”
The key is integrating benchmarking. It’s THE most critical aspect of dashboarding (and it’s something that spreadsheet views do terribly). Every dashboard and metric should have a frame of reference so that key risks and opportunities jump off the page. The two primary benchmarking elements you want to incorporate into dashboards include:
1) Performance relative to “others” at a snapshot in time. A customer stratification dashboard is ideal because it visually maps a customer’s overall performance (for better or worse) against its peers.
2) Performance trends over time, comparing how a customer is doing in the current period relative to a previous period.
These benchmarking elements are critical because while a “Core” customer may continue to outperform other customers, even a slight dip in any aspect of performance with such an important customer may signal the need to intervene quickly.
Benchmarking has the added benefit of making metrics more powerful and personalized for the consumer of the insight – whether that be:
- The salesperson (comparing performance relative to other salespeople)
- The customer (understanding performance relative to other customers)
The more you customize dashboards and insights to make them relevant to the user, the more likely the user will take action. Psychologically, no one likes coming across as an underperformer, and it’s surprising the lengths that sales reps (and customers) will go to reverse performance to fall in line with their self-identity.
Key principle #2: Provide better drill-down capabilities
Another core tenet for making dashboards consumable is the ability to slice and dice performance at a granular level . It always surprises me when companies don’t have drill-downs into product categories and subcategories or drill-downs of customers into market segments. The common excuse is that their ERP doesn’t incorporate that level of granularity and they haven’t yet prioritized manually creating those mappings for use in dashboards outside their ERP. This is not something you can afford to procrastinate. The insights gleaned from granular drill-downs are invaluable.
For example, wouldn’t you want to know if a drop in purchases of a given product is related to an overall decline in a product category or if it’s simply a rotation between different products within that category? Perhaps it’s an indicator that certain vendors or products are more “on-trend” than others. Wouldn’t it be powerful to be able to share those insights with customers? Similarly, wouldn’t you want to know whether a dip in performance is specific to certain market segments? Perhaps competitors are poaching a particular market segment with an aggressive campaign.
In addition to basic product-category and customer-segment drill-downs, there’s a wealth of other potential drill-down categorizations that you can develop and use to assess performance and differentiate in the market. For example:
- Flagging and tracking the relative performance of “new” vs. “existing” vs. “lost” customers (or vendors/products).
- Tracking performance of products within and across key buckets such as “private label” or “made in America.”
- Highlighting the relative performance of customers as gleaned from stratification ranks (“core” vs. “service drain” vs. “marginal” vs. “opportunistic”).
Granular insights can be powerful when identifying risks, prioritizing opportunities, and developing selling points with customers.
Mistake #3: Not integrating analytical insights into your sales team’s workflow
Solution: Early involvement, input and observation.
This mistake is critical when it comes to getting sales to consume and use data-driven insights. Introducing new analytics represents a change, and people tend to fight change. The goal is to eliminate as much friction as possible to improve adoption.
Communicate with sales as much as possible before introducing new analytical insights. Talk about what you’d like to convey, but at the same time, ask for their input and feedback.
It’s also essential to understand how analytical insights fit into sales reps’ workflows. When management shares reports with sales, they often overlook the fundamental challenge that sales reps have when switching from one application to another to view those reports. If it’s hard to switch applications, sales reps are not going to do it.
There are a few simple guidelines to integrate analytics into sales reps’ workflows successfully:
First, if you have inside sales reps or even outside sales reps that still spend time in an office, arm them with multiple monitors – at least two and possibly three. Ideally, they should use one for email, one for your ERP, and the third as a browser window to access analytics dashboards and your CRM. Asking sales reps to switch back and forth between applications on a single laptop screen when communicating with customers is a surefire way to reduce adoption of analytics.
Second, analyze how long it takes sales reps to access the information they need to make a decision. At the extreme, delivering spreadsheets or PDFs to users via email is the worst. It requires salespeople to find the email and then worry about whether it’s updated. Web-browser accessible “dashboards” are a better solution, provided that you design them as summary insights with quick drill-down capabilities. Again, stratification dashboards are the most effective way to deliver critical insights in the fewest number of “clicks.”
Third, “workflow” doesn’t just apply to day-to-day decision-making. It also applies to medium- to long-term sales management and planning. It’s essential to understand how analytics will enter the sales managers’ equation when conducting salesperson account reviews and performance reviews. Creating dashboards and scripts for sales managers to regularly review with sales will foster the adoption and usage of analytics. Just as importantly, it will encourage a more proactive sales approach and prevent reactive firefighting.
In conclusion, analytics-driven decision-making is not a Field of Dreams. It’s not “if you build it, they will come.” The analytical insights you provide, how you present them in dashboards, and how you integrate them into your sales reps’ (and sales managers’) workflows ultimately dictates whether data-driven selling can become a reality and help you drive profitable growth.