How IBM makes use of knowledge to energy its account-based advertising technique
My neighbor was a mathematics professor at a university in San Francisco. He once told me: “The longest distance between two points is through a committee.” »
His quote applies well to B2B sales. A Forrester survey found that 80% of respondents say at least three people are involved in the buying process, and most of the remaining 20% say they buy in teams of two.
Caitlyn Woodchief data scientist at IBM, says it’s essential to shift your B2B marketing strategy from targeting individuals to focusing on the account level.
During his presentation to Marketing Analytics and Data Science (MADS) ConferenceCaitlyn compares B2B buying to a family buying a house. Although parents are the ultimate decision-makers, they are not the only ones involved in the process. “The teenage daughter may want a larger bedroom, or maybe she wants to live near a playground for the son, or maybe she wants a nice fenced yard for the dog “, she explains.
In a B2B environment, decision-makers and other players in the purchasing process have different needs. IT wants a product that complies with cybersecurity standards. Engineering wants an API to extend the product, and marketing wants the ability to have easy to create dashboards.
“In the typical lead-based (marketing) model, you look at individual interactions with people, but in a B2B context, you really need to have a holistic view of what’s happening within an account, and not just these little slices. says Caitlyn, who creates data science models for sales and marketing at IBM.
Read on to learn his account-level methodology for renovating your B2B marketing strategy.
Follow a high-intensity account framework
When multiple people in an organization consume your content, you can quantify their interest in your products and services. Caitlyn looks for accounts with multiple marketing interactions over a 30-day period. You can use one month or more, such as 90 or 120 days, depending on your sales cycle.
In the IBM sales pipeline, approximately 12% of accounts reach this multi-interaction status each quarter. About eight in ten accounts involve two or more people, and 87% involve multiple product areas. These accounts are four times more likely to turn into an opportunity within 30 days.
“We want to learn from accounts that consume our content quickly and lead to conversion fairly quickly,” says Caitlyn. “These are the accounts that say, ‘I looked at IBM, I really like what you do and I want to buy from you.'”
Once these high-intensity accounts are identified, marketing can invite them to events and encourage them to sign up for free trials or demos. Reps can also prioritize follow-up interactions because these accounts are likely to convert quickly.
The framework also allows marketing to better understand the journey highly coveted customers. Caitlyn explains: “We can look at what are the most likely pathways for our accounts to reach high intensity. Are there any sticking points there? Can we resolve these sticking points? Does this particular content really resonate with the financial sector in Germany? Can we edit this content towards other sectors or other geographical areas?
Prioritize and highlight templates for sales teams
Remember the family that bought a house? A real estate agent showed them homes that met the parents’ needs and the children’s desires: a large second bedroom, a fenced yard and a location near a playground.
In B2B, marketing and sales play the role of the real estate agent, meeting the wants and needs of multiple buyers in the process. Caitlyn says the journey might look like this:
At the beginning of January, potential buyers viewed a research report. Then a few people in the organization did a free trial. A member of management and others attended an event hosted by the seller. In February, other members of the organization conducted another test.
Given the increase in account activity, marketing and sales teams would evaluate interactions and adapt their follow-up conversations and activities accordingly.
“It’s not just about one individual. It’s not just a trial,” says Caitlyn. How do these products interact with each other? How do they fit together? What is this account really about? And can we tailor our conversations to best meet their needs? »
Use data to optimize high-impact journeys
Caitlyn’s study of high-impact account data revealed interesting patterns, which she used to improve the customer journey with IBM.
More than half (54%) of prospects whose first interaction with IBM is a trial followed by consumption of a research report are identified as high-intensity accounts. Yet only 26% of prospects who simply try out are likely to become a high-intensity account. Similarly, prospects who received a research report within a week of a product demo were 3.2 times more likely to become a high-intensity account.
The data showed Caitlyn that the research report provides important background and context for the product being tested or demonstrated. Prospects might think, “I’ve tried the product and trial; I kind of get it, but then this research paper comes along and explains all the benefits that I didn’t really see in the essay itself.
Use data science to find more high-intensity accounts
IBM doesn’t just use data to maximize the journey of current prospects; it analyzes the data to find new accounts that resemble these high-intensity accounts, also called lookalike accounts.
He builds the strategy under the assumption that low-engagement accounts have not yet reached the content that will propel them into the high-engagement category. Blockers to accessing this content can be as simple as a broken link or the inability to follow up on a research report after a demo, Caitlyn says.
To find similar accounts, IBM uses positive label-free learning, a type of machine learning that uses positive (i.e. high-intensity) accounts, along with unlabeled accounts. It analyzes unlabeled accounts (typically low and medium intensity) to determine whether to label them as high intensity.
“We’re not yet trying to predict who will be high-intensity, but who is similar enough to our high-intensity accounts that we think they should behave similarly, and we can incentivize them to continue discussions with us,” Caitlyn explains.
Positive, unlabeled learning uses market activity, third-party industrial datageographic/market data and historical purchase data in the analysis. Caitlyn says it accurately identifies low engagement accounts that can be grown to high intensity 93% of the time. These similar accounts also convert twice as much as the average account.
Add account lessons to the system
After identifying high-intensity and similar accounts, ensure account information flows properly through sales and marketing systems. Here’s an overview of how IBM does it:
High-intensity accounts are passed to the sales rep to execute the inbound action from the Salesloft system at a cadence for the next best actions, leading to conversion.
The lookalike account triggers marketing actions that could drive Salesloft’s outbound cadence to generate additional activity or initiate the nurturing email flow through Marketo. This new activity could convert the similar account into a high intensity account. Then the new high-intensity account is routed through this process.
Are you ready to focus on account-level insights?
If my neighbor was moving from academia to B2B marketing, he would say something like this: “The path from investigation to close runs through a committee, so identify the groups making up that committee and understand what’s important to them. »
It used to be that if the chief information security officer of a Fortune 500 company downloaded a white paper, the brand’s marketers would jump up and down, thinking it was the start of a big sale.
But don’t get so excited about a C-suite download. This CISO may have their signature on the purchase order, but they likely have a committee of three to ten or more influencers who collectively decide on a vendor and product offering. Just like parents buying a new house, the interests of daughter, son and dog are of great importance.
As the IBM journey Caitlyn shared proves, it makes sense to move from individual to account-level information. Use the data obtained from researching high-intensity accounts to identify new accounts that can be converted to high-intensity accounts.
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Cover image by Joseph Kalinowski/Content Marketing Institute
