RevOps Co-op Weekly #45 - Revenutopia! How data can bring sellers and marketers together to route, prioritize, and drive high-quality pipeline.

Demandbase joins us to talk about why Account-Based Experience (ABX) makes sense for B2B, what you’ll need, and how to get started.

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Revenutopia! How data can bring sellers and marketers together to route, prioritize, and drive high-quality pipeline.

What You Need to Make Account-Based Experience Work for You

Check out the recorded webinar or some key highlights in the article below of Demandbase’s presentation on what Account-Based Experience is, why your B2B org should adopt it today, and what you can do immediately to get started implementing this strategy.

What Is Account-Based Experience (ABX)?

We've all heard ABM or Account-Based Marketing thrown around the office. ABM involves a very targeted investment in marketing to a select group of accounts.

It's how sales has always done things because there are only so many hours in the day for one-to-one interactions. It forces marketing to think long and hard about what their key prospects care about so they can tailor messaging and creative for maximum appeal.

Unfortunately, not very many of us have seen it work.

A common point of failure is the lack of agreement on the definition of a target account. Getting buy-in from sales isn't easy, and too often, marketers with a lead quota get tired of negotiating and ship the campaign before buy-in is obtained.

This means sales may not follow up on all of the leads.

Which means marketing just wasted money.

Account-Based Experience (ABX) is a company initiative to reallocate budgets dedicated to broad tactics and focus the spend on a small set of ideal accounts. This involves buy-in from the entire go-to-market wing of your company. Once the targeting is done, the collaboration continues with coordinated messaging and a plan for what each step of the customer journey should look like, from personalized messaging on your website to the way the Customer Success team nurtures them for future opportunities.

Like RevOps, ABX demands a coordinated approach and tends to gain momentum more often than not because the entire leadership team is all in. However, it also takes more work than a siloed attempt to get right.

Ready, Aim, FIRE

Remember when I mentioned that a common point of failure for ABM is disagreement on the definition of a target account?

Ideally, ABX not only leads to an agreement on your ideal customer profile or targets. It should also involve feeding data to your team to better equip them to have better interactions with these target customers.

Demandbase promotes the use of the acronym FIRE.

When instrumented properly, FIRE can be used to refine your targeting, personalize your messaging, and predict your odds of success.

Pretty cool, right?

Let's break down each element in more detail.

Fit

Fit, or ideal customer profile, is your ideal buyer's firmographic and demographic data in your ABX campaign. This list of prospects shouldn't encompass every use case and buyer profile you could sell to. Instead, this list should be informed by historical opportunity data and include a profile that is most likely to buy from you.

Let's say you sell cloud data storage and your company has four use cases it does well in:

  • Genomic mapping

  • Autonomous vehicle research

  • Medical imaging

  • Media rendering

Each of these use cases falls into very different markets. For an ABX campaign, we recommend you start small and choose one of the profiles because each has a different buyer committee profile with different problems that need to be solved. Then, you can change your ABX profile to fit a new market once you corner the market in one vertical.

Keep in mind you aren't just selling to one person at an account. You're likely developing 8-10 profiles to fit the buyer personas that make up your buyer committee.

Intent

Intent data provides a wealth of great information about an individual or company's buying signals. In our example, companies that meet our Fit profile researching "digital storage for autonomous vehicles" would be sending a powerful signal that they are in the market for our solution. In that case, we can use Intent to see which companies and even people we should engage with through advertising, personalized email targeting, and sales prospecting activities.

Relationship

Companies with a connection to your own have an increased likelihood of buying your product. "A connection with someone at your target company can give you a 44 to 84% increase in close rate. If you have connections within that buyer committee, that's a massive improvement. What wouldn't you give to double, or even grow by 50%, the amount of close wins that you have?" said Adam Perry, VP of Customer Experience at Demandbase.

So why not go down your list of Fit accounts and figure out if you have any coworkers with a meaningful connection with the people you're targeting?

When you combine Fit and Intent data to figure out which companies you should target first, you can run through your list much more efficiently and provide your team the suitable materials to make an impact when they reconnect with that person.

Engagement

The best advertising dollars are spent on accounts that are the right Fit, show strong Intent signals, and have a Relationship with someone at your account. Once you know who to target with which message, you can tailor your advertising for maximum impact.

Hopefully, you can see how each step in FIRE leads to a subsequent step and informs your go-to-market motion. Content, emails, and conversations can be tailored to focus on the things they're researching that are passed to you through Intent providers and which content they're Engaging with on your website. People displaying all of the signals in FIRE should be at the top of your predictive scoring models and flagged for follow-up by sales because they are the most likely to buy.

The Right Tech Is Everything

The ability to execute the FIRE method is predicated on investing and properly implementing the tools necessary to capture and capitalize on critical data.

For example, you can't adequately personalize your messaging if you don't understand where the person engaging with your content at company X is sitting in the world. The corporate headquarters might be in Chicago, but they're based out of Shreveport, LA. If you want to send them a team jersey as a thank you, you need to know which team they're rooting for. A Saints fan will probably burn a Bears jersey.

To make ABX work, you will need good enrichment tools that passively assign information to your contacts in your CRM to determine fit. You'll need Intent providers to give you information on which companies are sending which buying signals. You'll need webloggers or vendors who can tell you who is engaging with which content, and ideally, a data warehouse that can store a bunch of data.

"You are 300% more likely to get a customer convert from anonymous to known if you engage with them in the first five minutes you're on the web," said Adam.

Your tech stack strategy needs to extend beyond data enrichment and collection. You also need to curate a user experience that is on point from the moment they hit your website. This means leveraging your rich data to personalize your website to deliver the content that is most likely to hit a home run with the target looking at your home page right now. Of course, you'll need to think about your chat experience, too!

The more information you can deliver to your team in a meaningful way, the better. But perhaps even more importantly, use your data to celebrate and socialize your wins.

‍Watch for Predictive Buying Signals

Account-Based Everything doesn't stop once your first deal is Closed Won.

You have to equip your customer success team to provide an excellent customer experience and watch for satisfaction and dissatisfaction indicators.

Establish a customer scoring program owned by customer success to determine whether a company is likely to renew and recommend your company. Connect your product to your data warehouse to understand who is engaged with the product and who isn't. Then, automate predictive scoring that looks at what kind of help documentation your customers are looking at, whether they're researching new features, and if they're actively engaged and logging in.

While it's tempting to build in every signal to your predictive models, Adam warned us to stay small. The more indicators you add, the more likely you are to dilute your scores inadvertently. Use the most vital indicators that you have verified are tied to a future event and keep it simple.

Predictive models don't just help you identify a potential upsell. They help you prepare for competitive risks. 

No one wants to be told that a customer is doing a vendor review. This doesn't usually happen when the customer is thrilled with the product. Get the red flags that something isn't right early, so you have an opportunity to fix the problem before it balloons into churn.

Whenever you build a model intended to help any customer-facing facet of the business, get feedback often and communicate how you've incorporated that feedback into your model. At the very least, share data that conflicts with the popular theory so you can hash out whether or not there's a problem publically. The more you communicate and socialize your ABX wins (and improvements!), your buy-in will be stronger.

Watch the full Recorded Webinar here 👉 Revenutopia! How data can bring sellers and marketers together to route, prioritize, and drive high-quality pipeline.

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For more on Account-Based Experience, check out Demandbase’s comprehensive book on the topic here.

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