Even though there is a ton of interest in running ABM campaigns, there are still obstacles that can hinder performance. In addition to account selection and messaging, the biggest obstacle is often accurate campaign measurement. It's important to remember that without effective measurement set up at campaign deployment, true business impact will be nearly impossible to understand.
We cover:
-How to calculate the ROI an ABM campaign can give your specific company
-How to effectively adjust your ABM campaigns on the fly
-The attribution models most effective at measuring ABM success
and more!
Download the new ebook "How to Measure ABM from Start to Success" at engagio.com/measure-abm
Learn more about Engagio at Engagio.com
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3. But first, introductions
3
Charlie Liang
Director of Marketing
Engagio
Jordan Con
Product Marketing Manager
Bizible
Bogdan Zlatkov
Content Marketing Manager
AdRoll
4. Agenda
4
Pre-check - Is ABM right for you?
Health check - Mid Campaign Metrics
Final Verdict - Was it worth it?
12. Length of Sales Cycle
How long is your typical sales cycle?
0-3 months?
3-12 months?
12-24 months?
More than 24 months?
12
13. Length of Sales Cycle
ABM uses _________________ to speed up the sales cycle
a) Hyper-targeted account list
b) Highly personalized content
c) Multiple channels working together
13
27. ⠂ There are 2 main types of personas in buying cycle:
⠒ Decision Makers
⠒ Influencers
⠂ It’s important to engage your influencers early in the sales
cycle
⠂ Be sure to treat your prospect like an account and not a party
of one.
The importance of influencers
If influencer engagement is decreasing, you want
to adjust your content and messaging.
27
30. A/B testing is always a good idea, especially when a 10% or 20% uplift can make a big difference.
We recommend testing the following items in your creative, one to three variables at a time:
Intra-channel measurement
You don’t want assets to be out there for longer
than three months, and it’s best to refresh
graphics every month or two.
30
COPY CREATIVE
CALLS TO
ACTION
● Length
● Tone
● Font
● Colors
● Images
● Type (PNG
vs. GIF)
● Offers
● Text
● Colors
32. How to interpret the data
32
Heatmap of people who responded to a given campaign at target accounts
33. Some more tips for interpreting the data:
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DO IT IN A
GROUP
YOU DON’T
NEED A STATS
DEGREE
COME UP
WITH
TAKEAWAYS
KEEP IT
SIMPLE
USE VISUAL
CHARTS
34. What to show executives
How do you measure the art of ABM?
34
Tier # of Accounts Awareness MQA
Sales
Appt Opps
Pipeline
ACV
Conversion
to Opp
C/W
Deals
C/W
ACV
Conversion to
C/W
Tier 1 # # # # # $ % # $ %
Tier 2 # # # # # $ % # $ %
Tier 3 # # # # # $ % # $ %
Key:
MQA = Marketing Qualified Account
ACV = Average Customer Value
C/W = Closed Won
35. A critical mistake even great
organizations make is to engage
only one person at their target
account.
37. Was it worth it?
Which metrics could be misleading?
What should be getting better?
How do you use proper attribution?
37
38. Misleading Metrics
“This isn’t working. Ever since we started using ABM our
lead count has gone down!”
ABM may generate fewer leads
38
39. Misleading Metrics
Are you engaging with the right people at target accounts?
Are you talking to enough people within each account?
Is your internal champion in a position of influence?
39
Instead, measure these:
40. Misleading Metrics
“My conversion rate seems low—shouldn’t I be closing
more leads since my list is super targeted?”
ABM should have a high account conversion rate
40
41. Misleading Metrics
Are you measuring your conversion rate based on
accounts rather than leads?
Is your attribution model accounting for influencers in
addition to decision-makers?
41
Instead, measure these:
42. Misleading Metrics
“We’ve only closed 15 accounts with ABM, we used
to close 30 accounts!”
ABM isn’t necessarily about closing many accounts
42
43. Misleading Metrics
How much revenue did your closed accounts generate?
How does your ABM revenue compare to your lead gen
revenue?
43
Instead, measure these:
44. Metrics that should be improving
44
Velocity Deal Size Conversion Rate
Faster Bigger Better
46. Adjusting Attribution Model - Bad
Single Touch
100% Lead-creation (First Touch)
OR
100% Opportunity-creation (Last Touch)
By definition only gives credit to one person at one stage of the buyer journey
46
47. Adjusting Attribution Model - Better
Traditional W-shaped
30% (Anonymous) First-touch
30% Lead-creation
30% Opportunity-creation*
*Doesn’t measure past opportunity creation
47
49. Adjusting Attribution Model - And Even Better!
Custom is best of course!
Be sure to measure at the account level*
*especially for conversion rates
49
Why does it matter how many stakeholders there are in a deal?
If you use traditional advertising you might reach 10,000 or 100,000 people
But if you’re only reaching 2 people at each company, you won’t reach that threshold of 5 people needed to sign off on a deal
Of course, a salesperson can eventually get enough stakeholders to buy in to your product, but it’s a much slower process.
You can usually tell how many stakeholders you need to reach by the size of the deal you’re trying to close.
If you’re selling a $5,000 per year product, chances are there’s maybe one buyer who is getting approval by their manager to make the purchase.
If you’re selling something that costs $100,000 a year, you can be pretty certain there’s an entire team that’s deciding whether it’s worth that large of an investment.
There are really 3 main advantages of ABM
^^
This is something that salespeople do in their outbound outreach already.
Now we’re just using this same effective technique for the marketing team as well.
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While you’re in that survey window, go ahead and answer this question.
Don’t worry I won’t make you guys answer this one, because I think the answer is pretty obvious.
The answer of course is all of the above.
ABM uses a hyper-targeted account list that we show highly personalized content to through multiple channels.
I know that can sound very vague and involves a lot of marketer speak,
So I thought I would share an example with you guys of how we used AdRoll ABM to promote our own ABM product.
Above you’ll see our sequence for one of our SDRs named Dale.
After setting up our target account list, we had our Dale send outbound emails to each person on the target list.
If someone clicked on the outbound email they would get retargeted super frequently by the ads for 24 hours.
Then if someone clicked on the “let’s chat” in the ad they would be taken to Dale’s personal landing page where they could book a meeting with her.
So you can see a few important things here:
We’re starting with a very vetted hitlist of people we want to reach out to
We’ve created custom ads that speak directly to them
And we’ve reached them across multiple channels including email, social and the web.
So here are a few of the takeaways that you can see with ABM.
Forrester research found that...
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Most marketers would agree that the term “engagement” is being thrown around loosely. The problem is that it has deviated from its original intention and definition as it applies to ABM.
At its core, engagement describes something fundamental about the customer’s connection to your brand. Higher degrees of engagement mean a deeper connection and, potentially, greater commitment. Said another way, more engagement is a sign of a more meaningful relationship.
Before someone spends money with you, they’ll spend time with you. The more time they spend, the more interest they’re showing in doing business with you, which is why we at Engagio measure and score accounts by “engagement minutes.”
The touchpoints in ABM are essentially the same as they are in lead-based marketing, but with one major difference: touchpoints should be account-centric, and everything should be taken into consideration when looking at an account.
Take the example above. Notice that there are no people associated with this chart, so we’re looking at the account as a whole. This is critical because according to the CEB, there are now 6.8 buyers in the average B2B deal. If you’re using a lead-based approach, you’ll look at leads independently. That means that it will be very hard to piece together all the different touchpoints into a cohesive sale.
People matter in a deal. This is the core of account-based marketing, and it’s why we care when the touchpoints are happening and with whom. Departmental engagement is critical, because not only do we want to be in touch with people in positions of authority (CXO, VP, etc.), but we also want to be talking to the people in the right departments. For example, if you’re selling primarily to marketing, sales engagement doesn’t hurt, but it shouldn’t be viewed equally to engagement from the marketing team.
The chart below illustrates an example of how engagement can flow at an account. It’s important to see when the spikes in engagement are happening because those are correlated with important account milestones, like MQA, Opp Created, and Opp Won.
The touchpoints in ABM are essentially the same as they are in lead-based marketing, but with one major difference: touchpoints should be account-centric, and everything should be taken into consideration when looking at an account.
Take the example above. Notice that there are no people associated with this chart, so we’re looking at the account as a whole. This is critical because according to the CEB, there are now 6.8 buyers in the average B2B deal. If you’re using a lead-based approach, you’ll look at leads independently. That means that it will be very hard to piece together all the different touchpoints into a cohesive sale.
People matter in a deal. This is the core of account-based marketing, and it’s why we care when the touchpoints are happening and with whom. Departmental engagement is critical, because not only do we want to be in touch with people in positions of authority (CXO, VP, etc.), but we also want to be talking to the people in the right departments. For example, if you’re selling primarily to marketing, sales engagement doesn’t hurt, but it shouldn’t be viewed equally to engagement from the marketing team.
The chart below illustrates an example of how engagement can flow at an account. It’s important to see when the spikes in engagement are happening because those are correlated with important account milestones, like MQA, Opp Created, and Opp Won.
There are usually two main types of personas in a buying cycle: decision makers and influencers. Most direct marketing campaigns target the primary decision maker, but what often gets overlooked is the important role of influencers.
Think of the last product your group purchased. Were decisions made in a vacuum? Or was there a group discussion? Chances are, there were meetings, and the product was compared and contrasted with similar products before the group reached a buying decision.
It’s important to engage your influencers early in the sales cycle because they often have a lot of sway in that group decision-making process. This is a critical mistake even the best organizations will sometimes make—be sure to treat your prospect like an account and not a party of one.
Your influencer campaigns should be reviewed against your decision-maker campaigns to understand the effectiveness of each. You may want to tag each campaign differently to isolate them as you review marketing metrics.
Programmatic spend should be measured against its own channel for what we like to call intra-channel measurement and also against other channels for what we term inter-channel measurement. You should be reviewing these metrics weekly.
Individual channels need to be optimized to perform their best. You should understand how well offers are performing within their own peer groups, as well as micro-optimizing campaigns and testing for impressions, clicks, and acquisitions or downloads.
Generally, intra-channel KPIs are more tactical, since you’re optimizing them at a micro level. You generally also don’t want assets to be out there for longer than three months, and it’s best to refresh graphics every two month or two (if you have the resources to do so). There are diminishing returns on every graphic and offer, so keep your content fresh.
A/B testing is always a good idea, especially when a 10% or 20% uplift can make a big difference. We recommend testing the following items in your creative, one to three variables at a time:
Copy
Length
Tone
Font
Creative
Colors
Images
Type (PNG vs. GIF)
Calls to action (CTAs)
Offers
Text
Colors
Inter-channel measurement is a bit tougher in the sense that the metrics across channels vary more. For example, you may measure the impact of executive dinners differently than you would social media ads and personalized outreach.
The key to inter-channel measurement is to find common metrics that all campaigns can be held accountable to.
Engagio has published an entire ebook around this, but here are the top four metrics for ABM success:
Coverage. Do you have sufficient data, contacts, and account plans for each target account?
Awareness. Are the target accounts aware of your company and its solutions?
Engagement. Are the right people at the account spending time with your company, and is that engagement going up over time?
Influence. How are the ABM activities improving sales outcomes such as deal velocity, win rates, average contract values, retention, and net promoter scores?
Also, since ABM is by definition account-centric, all the metrics change. Specifically, all person-level metrics should now be assessed at the account level.
Whether you follow the SiriusDecisions model or a different one, it’s important to look at key account milestones across channels. For each campaign, set goals for how many MQAs, meetings, opportunities, and new leads you’d like to achieve.
Interpreting data is perhaps the most challenging part of successful ABM measurement. For optimal results, it’s best to look at the data without any bias, rather than trying to find data that supports a preconceived conclusion.
This is an example of a scorecard you’d want to keep at key accounts. The numbers correspond with the total number of people you have in the database for a given company (both leads and contacts) and how they’ve progressed through milestones for this given campaign.
With these visuals, you’ll be able to easily spot where to double-down on your efforts in terms of getting accounts to engage.
Here are some more tips for interpreting the data:
Do it in a group. People draw different conclusions, so ask a colleague to go through the data with you to make sure nothing has been missed.
You don’t need a stats degree. It’s important to know the general concepts, like statistical significance. But B2B sample sizes are generally smaller, so directional significance works much of the time.
Come up with takeaways. Data is just data if you don’t use it in a meaningful way.
Use visual charts like the ones above. Most people fare better if you display the data in an easy-to-read manner. Try color-coding things.
Avoid jargon and keep it simple. Especially when dealing with executives.
These days, marketing leaders are fluent in metrics, analytics, and reporting. Marketing technology has enabled marketers to measure every single action a prospect can take, turning conversion into a science.
However, with the transition to account-based efforts, we need to reconsider how to think about reporting metrics to the executive team and the board. Since there’s a greater focus on quality than quantity in ABM, you must balance the art with the science.
Therein lies the problem—how do you measure the art of ABM?
Here’s a simple template inspired by ABM ops pro Kristen Wendel of LeanKit. In addition to adopting this ourselves, we now encourage all of our customers to use it when reporting to the board on ABM.
I’m here today to talk about the final verdict — essentially, did the outcomes of your ABM efforts merit the investment? These are the things your CMO is probably on the hook for, things the CEO and CFO care about, etc.
First, we’ll cover some metrics that you might be more familiar with, but I’ll talk about why they can be misleading when it comes to ABM. Then, we’ll cover the right metrics, and then we’ll dive deeper into attribution, which is how you track, measure, and credit your ABM efforts using the metrics that matter.
Misleading metric #1: lead volume. “This isn’t working. Ever since we started using ABM our lead count has gone down.” Gone down or stayed flat, etc. The truth is, an ABM strategy may generate fewer leads. That’s because in an account-based strategy, it’s not about lead volume; rather, it’s about attracting the right leads. Quality over quantity.
Instead, you can look at more useful indicators that measure quality. These are a lot of the same things that Charlie talked about. Are you engaging the right people at the right accounts? Are you talking to enough people at each account? Is your champion in a position of influence. If your internal champion is an entry-level person, it’s going to be much harder to push the deal through compared to if your internal champion is the CMO or a VP. Engaging a marketing coordinator or a CMO both register as one lead, but there is a huge difference.
The next misleading metric is conversion rates. “My conversion rate seems low. Shouldn’t I be closing more leads since my list is super targeted?” The reason this is misleading is that if you’re calculating conversion rates based on leads, your numbers won’t add up.
Instead, you need to be measuring your conversion rate based on accounts. If you’re marketing to enterprises, you may have dozens of contacts engaged in a single account. All of those people can become one opportunity and one customer. For easy math, let’s say that you have 10 accounts with 100 contacts in each. That’s 1,000 leads. And let’s say that you convert all 10 accounts to opportunities. If you’re looking at it the old lead gen way, that’s 1,000 at one stage of the funnel, and 10 at the next, for a horrible conversion rate of 1%. But in reality, you were 10 for 10, a 100% account conversion rate.
Moving down the funnel, the next misleading metric can actually be the number of customers. You’re thinking, how can the number of customers you close actually be wrong? Another key component of ABM is targeting bigger deals.
Instead, you need to be measuring all up revenue. Rather than just volume of deals, it also includes deal size, upgrades on existing customers, etc.
Here are three metrics that should improve with ABM. Velocity is the time from opportunity to closed-won. Deal size is about closing higher value deals. And Conversion Rate or Win Rate is about closing a higher percentage of opportunities.
As you may have noticed, the final verdict comes down to revenue. The three metrics from the last slide are all components that contribute to revenue. Closing faster means more revenue, closing bigger deals means more revenue, and converting more opps to customers means more revenue. The other metrics we talked about are really important at optimizing execution, but ultimately, what your company really cares about is how much revenue your ABM programs are driving.
When you can accurately measure the impact of your ABM efforts to revenue, you can plan for revenue, and ultimately execute for revenue. So...when it comes to measuring revenue, how do you do it? Let’s talk about attribution models.
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The W-Shaped model is a great model for most organizations, especially as they start to roll out their ABM program. It gives credit to multiple touchpoints at various stages of the funnel. When it comes to measuring the engagement of multiple stakeholders or contacts within the account, it captures three frequent stakeholders: 1) the researcher who discovers your company, 2) the practitioner who downloads a white paper or registers for a webinar, and 3) the decision-maker who gets the demo. However, the flaw is that it stops at opportunity creation.
It measures multiple stages throughout the funnel. A huge component of ABM is that it empowers marketing to engage post opportunity stage. Without measurement beyond the opp creation, that won’t receive any attribution credit.
Match your model to your buyer journey - if you have a long sales cycle with many stages, you may want to have more key stages. This can also include post closed-won stages like upgrades and expansions.
We’ve built a machine learning algorithm that recommended percentages based on our attribution data, and then adjusted from there.