How to Perform an Effective Win/Loss Analysis

Posted by Lucrativ on 10/12/19 11:45 PM

 

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Conducting a win/loss analysis helps sales teams improve on their performance—so they can win more deals and cut their losses. Knowing the figures on your wins and losses and the reasons behind them is crucial for a team’s continuous growth.

The first thing you need for any analysis is data. So make sure to gather all relevant data for your win/loss analysis. While a win rate can be easily computed by simply dividing the number of won deals by total number of opportunities, there are other relevant data you need to generate more valuable insight. Among them:

Demographic Data: Gather demographic data on both the prospect and his company. Company demographic data include company size, industry, competition, revenue, and the like. Prospect demographic data include job title / role, job level, tenure, etc.

Psychographic Data: Psychographics relate to the individual’s personality, attitudes, values, interests, etc. Psychographics help you understand a prospect’s pain points, aspirations, and motivations for purchasing.

Sales Activity Data: All sales activities must be recorded or tracked. These include: calls made to prospects, emails sent, and meetings or presentations conducted for prospect. Feedback from these touches should also be monitored.

Buyer Behavior Data: Every time a buyer interacts or engages with you or your company, these behaviors need to be monitored. These include website visits (and which pages), emails opened, lead magnets downloaded, calls received, etc.

Opportunity Status Data: Has the opportunity been won? Lost? Is it moving along? Or is it still in limbo somewhere in the funnel?  Where is the buyer in the sales funnel or his buyer’s journey? A sales funnel analysis is helpful at this point: it shows the conversion between each stage or step. It analyzes the buyer’s journey and how he responds to each step in the sales process or sales funnel.

Closed Deals Assessment Data: What deals were closed? It would be best to analyze the process for these deals and determine the best practices for replication. Feedback from customers is important for the assessment.

Lost Deals Assessment Data: Similarly, lost deals must also be evaluated. What were the reasons the deal didn’t push through? Sales reps may not be as objective when identifying the reasons. When you can, get feedback from the prospects themselves.

Prospect Feedback Data: Feedback of any kind from prospects is very important. So make sure to monitor those too and record them. You may directly ask for feedback anytime during and after the sales process.   

Why do you need all these data? With all these data you can derive a lot of actionable insights. Additionally, all these data can you help you generate two kinds of analyses: quantitative and qualitative.

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Quantitative Analysis
This measures—and assigns numbers—to your wins and losses. You may compute for different win/loss rates that will measure your sales team’s performance across many factors and variables. Some of the key data points that form a quantitative analysis include:

  • Overall Win Rate: This is the percentage of opportunities converted into won deals. To calculate: divide your number of won opportunities by total number of opportunities. 
  • Win/Loss Ratio:This compares your wins against your losses. To compute: divide number of won opportunities by number of lost opportunities.
  • Competitive Win Rate: This computes for your success rate versus competition. Computing for this is similar to computing for your overall win rate, only you factor in competition. To compute: divide your number of wins you had against a competitor by number of total opportunities you had against a competitor.
  • Win Rate by Sales Segment: This compares success rates of different sales teams within your organization. You can determine which sales teams need more coaching and training from these data. This also follows the overall win rate formula, but sales segments factored in. To compute: divide your number of wins by one segment by number of total opportunities of that same segment.
  • Win Rate by Product: This is great for companies with several products or product lines: they are able to see which ones are really moving and which need more pushing. To compute: divide your number of wins for one product by number of total opportunities of the same product.
  • Loss Rate by Reason: Knowing why you lost a deal is one thing, knowing the stats on this is another. It will give you more reasons to re-strategize sales efforts. Reasons for loss may include lack of budget, more competitive pricing from another provider, tight deadline, etc. Compute your loss rate for each reason by dividing your number of losses due to one reason by number of total losses.

 

Qualitative Analysis
While quantitative analysis gives you the numbers to your wins and losses; qualitative analysis tells you the reasons behind your wins and losses. This is why feedback—from sales reps but more so from prospects—is very important.

You need to talk to your reps and prospects—those who converted and including those who did not. Formulate the questions you will ask them to gather the qualitative data you need. This may include:

  • What about the product made you decide to buy / not buy?
  • What did you like about the service rendered by the sales team?
  • What did you not like about the service rendered by the sales team?
  • Who made the final decision on the won / lost deal? What was their reason(s)?
  • If pricing was not an issue, which provider / vendor would you have gone with?
  • What would have made you purchase our product / service?

 

These are just some sample questions; there should be more specific to your product, service, and business model. And always remember to follow up with your questions. Hiring a third-party firm may prove more advantageous as you will achieve more transparency in the interviews.

Data and custom reporting are critical in a sales team’s success, and a win/loss analysis is something every sales organization should perform periodically—and perform it effectively.

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Topics: Sales Intelligence

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