One of the most popular channels of win-loss insight is sales team feedback.

When done right, this can provide an internal perspective on why you win and lose. To explore all of the potential channels of win-loss insight for your organization - and the pros and cons of each - download a free copy of The Definitive Guide to Win-Loss Analysis.

This mini-series explores three challenges that organizations typically face when implementing a win-loss reporting process in Salesforce CRM.

Part 1: The data we are collecting is not insightful.

Part 2: My sales team is not participating.

Part 3: The insights don’t translate into action.

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Part 1: The data we are collecting is not insightful.

Companies often struggle to gather insightful, useful win-loss data from their sales teams. In many cases the question methodology is too basic to yield meaningful insight (a single pick-list). In other cases, the question set is overly complex, which causes survey fatigue and forces reps to answer questions they don’t really know the answers to.

To strike the right balance, begin with the end in mind by asking yourself “what insights are most important to us?” Then, avoid these five common pitfalls as you structure your win-loss question set:

1. Unclear questions: One reason why data may not be insightful is that the questions used in the win-loss form are unclear. Many companies have reps select a won or lost reason from a pick-list field. While this is understandable for data uniformity, pick-lists limit the insight you could gather from your reps. They won’t tell the full story of why you won or lost a deal. For example, you may have lost a deal because of pricing gaps, product shortcomings, and a strong competitor. How is the rep supposed to select one reason? The pick-list response you get from the rep will not accurately answer the question “Why did we win or lose?”
2. Unnecessary questions: Win-loss forms should be simple and uniform enough that they apply to every opportunity. Don’t add in nice-to-knows, or questions that don’t apply to every opportunity. Creating conditional questions that only display when certain criteria are met will prevent salespeople from gaining familiarity with the question set. They make the feedback process painful, slow, and unpredictable which impacts the quality of their response. They also create inconsistencies in your data set when it comes time to build meaningful reports. Stick to the basics: Did we win or lose? Who did we win or lose to? Why did we win or lose?
3. Imbalance of good and bad: Most companies just ask "Why did we lose?" or "Why did we win?" This leads you down a path where you’ll only have positive feedback for wins, and negative feedback for losses. This doesn’t give you a balanced view of your strengths and weaknesses. Allow reps to provide balanced feedback such as “We ultimately won on product features, but our implementation timeline was rocky and put the deal at risk.” Think about how you can systematically gather balanced (positive and negative) feedback for each opportunity. If you’re not sure how, download a copy of The Definitive Guide to Win-Loss Analysis for examples.
4. Lengthy feedback forms: When developing your question set, how much is too much? Too few questions, and you’ll miss out on key insights. Too many questions, and survey fatigue or speculation - on the part of the opportunity owners - will hurt the quality of your data. As a rule of thumb, only ask one open-text question per closed opportunity. Then, keep the entire form to 5 questions or less. Make sure it takes reps less than 2 minutes to provide a response.
5. Limitations of native Salesforce functionality: It’s no secret – Salesforce has invested very little in terms of win-loss analysis and reporting. If you rely on native functionality in Salesforce, you’ll be limited to basic input methods like pick-lists or open-text fields. As a result, you’re likely set up to fail. If this is the case for you, consider other ways of engaging reps. Make sure that whatever process you use for internal win-loss data collection from your sales reps is flexible enough to allow you to collect insightful data.

The Clozd app for Salesforce streamlines the collection and reporting of win-loss data from your sales team, and can help you apply the principles outlined above. For example, this matrix-style question allows reps to quickly rate the positive and negative factors that may have influenced the outcome of the deal:

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To make your data more insightful, design questions that focus on these three things:

1. Outcome: What did the buyer actually do? Did they purchase your product? This is a win. Did they purchase a competitor’s product? This is a loss. Did they decide not to purchase anything due to external factors? This is still a loss, but it has very different implications for your business, so make sure you differentiate your loss types.
2. Decision Drivers: What were the relative strengths and weaknesses of your offering during the evaluation process? Multiple factors almost always influence a deal one way or another. Creating a list of common Decision Drivers will help your reps give more detailed feedback on why they won or lost a deal while still producing digestible, insightful data. This will prevent you from over-rotating on one specific factor because you allow the reps to give you a balanced view of the deal.
3. Primary Competitor: Who did you lose to or beat out? This is who really mattered. Don’t make the mistake of trying to capture every competitor who was involved in the RFP or evaluation. The reality is that reps likely don’t know who all the competitors were, but they should know who the primary competitor was. Also, give reps an option to say “I don’t know.” It’s better to acknowledge that than to collect bad data.

Remember, collecting data that is not insightful is simply a symptom that could be generated by a myriad of root causes. Solve the root of the problem and you’ll be on your way to collecting meaningful, actionable data.

Even if you’ve figured out how to collect meaningful data, your win-loss program may still suffer from other symptoms, such as low rep participation or not acting on the insights your data give you.

For the next article in this series, click here.