A closer look at your win/loss analytics

When the end of the year is just a few days away,what would you discover if you did a quantitative analysis of the data for every single deal that your sales people worked on during the year? What actions would you take to produce a different outcome as we turn the corner and begin anew?

Leading indicators

Your win/loss data should allow you to quickly identify the following key metrics for every member of your team:

• Win rate (%)
• Sales cycle length (number of days)
• Average deal size ($)

Let’s take a closer look at the average deal size. If you break down the data, you should be able to pinpoint a smaller range for where you win the majority of your deals. For example, your average sales cycle for all deals (won and lost) may be 100 days, but the majority of deals that you won in the last year might have a sales cycle ranging from 60 – 90 days (loss cycles tend to be longer; research shows that sales people spend up to 65% more time on deals they lose compared to those they win). Why is this important? Well, armed with this knowledge you can identify bad deals earlier going forward – if an opportunity has been in the pipeline for 120 days, has not had any real progress in the last month, and is not yet in the final phase of the sales process, it’s most likely not going to be closing.

We can apply the same analysis for average deal size. You will have an average deal size for all won and lost deals, but the majority of won deals will most likely have a smaller and more defined monetary range. Knowing what this range is will help you proactively (preferably before a prospect is converted into an opportunity) identify deals that your sales people should stay away from, on the basis that they are either too small or too big.

Why do you win and why do you lose?

In order to make informed, data-driven decisions about which deals to pursue, we need to dissect the main reasons for why we win and lose opportunities.

Why did we lose deals last year? Did we keep involving ourselves in opportunities where our products and services were a bad fit for what the customer was looking to achieve? Were we going for opportunities that were too big, where we did not have the resources required to deliver in line with expectations?

Perhaps even more importantly: why did we win? When reviewing our results, we naturally need to understand our losses. However, we also need to analyze the types of deals that we won, so we can go after opportunities with similar characteristics in the future.

Maybe we win the majority of deals because we managed to establish ourselves as trusted advisors, or because of our excellent service delivery. If we fail to look at the data, we’ll fail to identify the opportunities where we can play to win and end up wasting a lot of time, money and resources on deals with little chance of closing.

Win rate influencers

Having identified the main reasons for why you win and lose deals, try to pinpoint any recurring deal characteristics that had a significant influence on your wins and losses. This could be related to your customer profiles: you may have a much stronger win rate when targeting companies of a particular size with a certain range of annual revenue that operate within particular industries or geographical locations.

However, you may also identify other tangible facts that have a significant bearing on the outcome - for example, your win rates may drop significantly when you face a particular competitor, or when there is a tender process involved. Conversely, your win rates may skyrocket when deals involve a particular trigger event, such as a merger or expansion, or when the customer has been referred to you from within a particular network.

Other key indicators

Time in stage

For a closer look at how well your sales people adhere to executing a sales process in the field, compare and contrast the velocity for your won and lost deals. Your won deals may very well flow through the pipeline at a somewhat predictable pace, whereas lost deals take longer to proceed and get stuck more often.

Stalled

In complex sales, deals stall. However, the average time a deal stalls at any point of the sales process will most likely be shorter for won deals compared to those you end up losing. For example, let’s say you uncover that the majority of won deals stall for no more than 17 days (at any given time in the sales process), but your lost deals continuously stall for 30+ days. Once you have uncovered the specifics, you will be able to critically evaluate each opportunity in the pipeline against these criteria on an ongoing basis.

Where to from here?

Conducting a win/loss analysis is a great way to dissect relevant deal data and identify the commonalities for your won and lost opportunities. To help you get started with a quantitative analysis, we have prepared a short checklist

1. Identify the win rate, average deal size and average sales cycle for everyone on your sales team

2. Take a closer look at your won deals – during what time range did the majority of them close? What was the deal size range for these opportunities?

3. Identify the top 3 reasons for why you won and lost deals over the last year

4. Identify the top 3 opportunity influencers for your won and lost deals last year

5. Compare the pipeline velocity between won and lost deals

6. Compare the average time your won deals stalled, in comparison to the deals you ended up losing

7. Using the data you have uncovered, document qualifying questions that your sales people should obtain answers to early on in the sales process

8. Constantly evaluate the opportunities in your pipeline against these findings to get rid of deals that have little to no chance of closing, so you can allocate the time, money and resources needed for the opportunities

To learn more about Membrain’s in-built Win-Loss analytics, contact us today on sales@membrain.com