B2B Marketing Blog

How To Perform Actionable Win Rate Analysis With Marketing Attribution

By Jordan Con
May 2, 2016

Win rate is an essential bottom-of-the-funnel marketing metric. Measuring win rates gives B2B marketers a constant gauge of how well marketing efforts are converting prospects, especially at the bottom-of-the-funnel. And on the Sales side, it gives insight into how the sales team can more efficiently make use of their resources as they try to close customers.

It’s a measurement that helps with marketing and sales alignment, making win rate a particularly important measurement in account-based marketing.

Measuring and analyzing win rates is critical. So how do you do it? This post will cover how to use marketing attribution data to perform accurate and comprehensive win rate analysis that you can take action on.

Win-Rate.jpg

Why marketing attribution data?

Marketing attribution connects marketing efforts to sales data (i.e. opportunities, customers, revenue) for a full-funnel view of marketing’s effectiveness.

And because it’s a centralized source of data, marketing attribution ensures that cross-channel or cross-campaign analysis (e.g. win rate analysis) is comparing apple to apples and is also not subject to double-counting errors.

When we look at win rates, we want to be able to use different marketing variables to see how they result in either a closed-won deal or a closed-lost opportunity. And ideally, we want to be able to use different levels of granularity. How do certain marketing channels impact win rates? What about campaigns? Keywords?

Only a sophisticated marketing attribution solution can accurately provide this level of data, from first touch to closed customer, let alone help marketers understand whether their campaigns and channels are “winning” at all.


Win rates

When we talk about win rates, we are measuring the ratio of closed-won opportunities to all closed opportunities (won and lost) within the same time frame.

Let’s say that we have 10 opportunities in trial this month. At the end of the month, five become customers and five become closed-lost opportunities. That would create a win rate of 50% -- five closed-won opportunities divided by ten total closed opportunities.

Calculating the win rate alone is easy to do and provides useful information. If we can increase our win rate, we can bring in more customers without changing our pipeline volume. Of course, it’s ideal to do both: improve win rates and increase your pipeline volume.

But the overall win rate alone isn’t very actionable. For win rate analysis to be actionable, you need to also be able to analyze the underlying factors. Are there any patterns in the customer journey of the five opportunities that became customers compared to the customer journeys of the five opportunities that were lost? What can we learn from them that will help us improve our marketing and sales efforts for future opportunities? This is where the powerful insight from win rate analysis happens.


Step 1: Pose a question

What do you think has the biggest impact on win rates? Do you have a superstar piece of content that you think drives high quality opportunities? Is there a specific bottom-of-the-funnel marketing activity that’s a good closer? Or maybe you want to find out if there’s a magic number of employees at a prospect company that you need to engage. This last one is particularly powerful for account-based marketing.

First, come up with a question that you want to analyze. Then, make a hypothesis to make sure that the potential answer to your question is actionable. If the answer to your question is something that you don’t have power to change, then the analysis won’t be useful.

A good way to start is by analyzing how different marketing channels or campaigns affect win rates. The results of these types of analysis will help you better allocate your budget (channel analysis) or adjust what type of campaigns and content you create in the future (campaign analysis)


Step 2: Identify the variables

The next step is to identify the different variables that you will have to test in your analysis. With channel or campaign analysis, it’s easy. The different independent variables will be either your marketing channels or your marketing campaigns. Your win rate will always be the dependent variable.

When we engage our prospects on X marketing channel, our win rate is Y.

When we engage our prospects with X marketing campaign, our win rate is Y.

When we engage X number of prospects within an account, our win rate is Y.


Step 3: Run your attribution analysis

Once you’ve identified the variables that you want to analyze, the next step is to run the attribution data and create a report that will give you your answer.

Again, win rate is calculated by:
Closed-Won / (Closed-Won + Closed-Lost) = Win Rate

So we need two opportunity reports and some simple math. For this example we will use the first question and hypothesis that we posed: How do our marketing channels affect win rates?

We want to find out if any particular marketing channels outperform the others when it comes to win rates. The answer to this question will help us to better allocate our budget in the future.

The first report that we will make will tell us the number of closed-won opps by marketing channel. The second report will tell us all closed opps by marketing channel. Using the data from these two reports, we can calculate the win rate ratio for each individual marketing channel.

An important thing to remember when creating your attribution report is to keep the time frame constant. Because the B2B cycle can take a long time from first touch to closed, if you are not consistent with how you set the time frame, you may end up working with two different data sets. For this example, we could use the Opportunity Close Date for Q1 2016.

Here’s what a simplified version of the report could look like (made up numbers):

CLOSED-WON OPPS

 

January 2016

February 2016

March 2016

TOTAL

Email

20

15

37

72

Events

64

10

15

89

Paid Search

20

27

21

68

Social

44

47

56

147


This report shows us the opportunity count for each marketing channel. When we run this type of report at Bizible, we use W-Shape attribution, which allocates credit across key touchpoints along the customer journey. This also means that the opp count will likely include fractions of opportunities. For example, if a closed-won opportunity had one email touchpoint, but the rest of the journey didn’t include email, email would be credited with 0.3 opportunities. For the sake of this example, we only used whole numbers.

TOTAL CLOSED OPPS (Combined Closed-Won and Closed-Lost)

 

January 2016

February 2016

March 2016

TOTAL

Email

50

30

80

160

Events

90

12

22

124

Paid Search

45

62

72

179

Social

80

77

102

259


Again, we have to use the same attribution model and time frame for this report.


Step 4: Make a conclusion / adjust your question and start again

 

Closed-Won

Total Closed

Win Rate

Email

72

160

45%

Events

89

124

72%

Paid Search

68

179

38%

Social

147

259

57%


Based on these win rates, it looks like Events are a powerful down-funnel channel, while Paid Search seems to be less effective. Some takeaways from this are how do change our Paid Search strategy to improve win rates? Do we need to spend more time optimizing possible nurture tracks for Paid Search leads or do we need to change our Paid Search campaigns? These are further analyses that we can do.

There’s a lot of further analysis we can now do to further understand events, as well. There are many different types of events -- sponsored conferences, hosted events, events where we have a speaking role, sales dinners, etc. With the insight that events have an exceptionally high win rate, we should investigate which types of events are working best and figure out why they are so effective. Then, we can invest more resources into the best performing events.


Step 5: Make the adjustment

The last step, once we’ve dug a bit deeper (e.g. identifying which types of events are performing well), is to make the adjustment and, in this case, invest more in doing events like those.

We are always searching for ways to improve win rates -- changing our marketing strategy, changing how we pick and choose which opportunities to really go after, etc. The adjustments that we make from these types of analysis all have the goal of impacting our win rates from all angles.

Of course you don’t just make the adjustment and end there. Win rate analysis is a process. As we said earlier, measuring your win rate gives you a constant gauge of performance. It’s something you need to continually monitor, analyze, test, and optimize.

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Topics: attribution

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