This article is Part III of a 4-part series on the shifting landscape of B2B buying and selling, how revenue teams have adapted, and where we think the market is headed.
You can read Part II, where we introduce account-based marketing and how it improves the buyer experience to get past the noise explained in Part I.
In the previous two parts, we talked about the problems facing revenue teams today and how we got there. Account-based marketing is a step in the right direction, as it adapts how companies engage with buyers depending on the stage of their buyer's journey.
Right message, right person, right time, through the right channel.
However, having implemented ABM solutions ourselves and talked with many current or former users of ABM, we've seen that there are hard setup and maintenance costs, as well as difficulties in running such a complex operation effectively - particularly speed, coverage, and consistency.
People are influenced into deals rather than pushed into them like before. Demand creation and dark social are starting to become a key part of people’s strategies.
Understanding Demand: Creation vs. Selling
(Image Source: Freepik)
Demand creation focuses further up the funnel at the awareness and consideration stages of the buyer's journey. It's about finding ways to get our brand in front of the 97 to 99 percent of our total addressable market who may not be actively in the market but have the potential to become prospects in the future. This involves utilizing channels like LinkedIn, Reddit, ads, webinars, blog posts, and influencers to educate and engage with our target audience.
Demand capture is about capturing the buyer in the decision and purchase stage. Again, only 1 to 3 percent of people are currently in the market and showing purchase intent. This is where all of our sales team's efforts should go. There's typically a high cost for sales spending time on accounts that are not in-market.
The need to split between demand creation (mostly marketing, though there can be some assistance from sales) and demand capture (mostly sales but with some marketing influence) is to fulfill the buyer journey experience.
One common mistake companies make is the tendency to allocate most of their budget towards demand capture, even though 70% of the buying journey has already occurred by the time a seller is involved. By then, the buyer already has a top 5 list of vendors they are looking to evaluate.
By neglecting demand creation, we risk commoditizing ourselves among competitors and miss the opportunity to distinguish ourselves as a leader.
If we truly solve a problem, our buyer will be in the market for our solution one day. And if we did demand creation right, they'll be googling for our solution via branded search terms rather than typing our category name, where we may not even rank in the first four search results.
The Importance of ICP Creation
When we look at the difference between high-performing and low-performing SDR teams, there’s one thing that stands out across the board:
The best teams are getting fed with better pipeline.
That is, the leads coming through are of higher quality. They’re a better match for the company’s ICP, so they have an easier time closing deals and waste less time on leads that would never close.
For this, you need to have your ICP clearly nailed down and ensure your demand-generation activities are tailored to that specific audience.
It is not just about finding a fit on demographics, though.
You also want to know that the company is growing. Do they have NRR over 100%? Are they retaining customers? Is revenue increasing?
If these signals are all met, it means you’re less likely to have churn issues in the future because the buyers got laid off.
Wasting Time on The Wrong Activities
The other problem with many low-performing SDR teams is that they aren’t focusing on the right actions. Only 20% of their time goes to activities that create progress. The other 80% is just wasted time.
They aren’t working on the right deals at the right time, with the right people, through the right channels.
Revenue orchestration helps sales teams prioritize the best leads and deprioritize the worst ones so they can work on the activities that actually move the needle forward.
Advantages of AI-powered Revenue Orchestration
Fit
AI-powered revenue orchestration helps ensure that the leads that do make it through to a conversation with sales reps are highly aligned with your ICP.
Instead of funneling all potential prospects through to a demo (like a standard chatbot or meeting booker would), a revenue orchestration solution:
- De-anonymizes the site visitor.
- Enriches your CRM data on that account with other firmographic info (such as identifying who else might be on the buying committee).
- Extracts third-party buying intent signals from external providers to understand where the prospect is at in their buying journey.
- Understands the current health of the company by pulling publicly available growth metrics.
- Matches that collection of data against your ICP construct to determine what conversational path to put them down.
- Orchestrates communications across email, social, and live chat.
- Nurtures the prospect until they demonstrate a sufficient level of intent, triggering an alert for a salesperson to take over.
This means those website visitors you aren’t a fit for your ICP don’t clog up your sales teams’ meeting pipeline, which translates to faster sales cycles and stronger conversion rates.
Speed
When a target company exhibits buying intent, the window of opportunity that the buyer is thinking about you could be seconds.
If a buyer visits the site and has a question about the product but is unable to meet with a rep until a day later, that may be too late if the budget discussion is tomorrow. By the time a sales rep reaches out, the moment may have passed, and the buyer has gone to a competitor.
Here's an example of how orchestration could solve this.
The VP of Marketing tells a B2B marketing manager at SaaS Co. to research an intent solution to get more in-market leads. SaaS Co's marketing manager asks the Pavilion Go-to-market community for alternatives to 6sense because 6sense is so expensive. Someone mentions Warmly.
The marketing manager visits Warmly's homepage, the case studies page, and the pricing page. On the pricing page, the chatbot pings - it's an AE at Warmly asking if they have any questions.
The marketing manager doesn't realize he's speaking to an AI. But by now, the actual AE has been notified and jumped in to take over the conversation, initiating a video call. They arrange to catch up again after SaaS Co's budget meeting (that's tomorrow). The marketing manager notes the solution in his deck and calls it a day.
But the orchestration doesn't end there.
- Immediately after, the SaaS Co.'s CFO receives a LinkedIn connection request. It's the Warmly AE, enquiring about their precarious financial position. They detail exactly how Warmly integrates into SaaS Co's existing tech stack and maximizes the ROI of marketing spend. The CFO ignores the message but keeps Warmly in mind.
- The rest of the buying committee (the VP of Marketing, CRO, VP of Sales, and Head of Sales Development) receive custom emails addressing all the risks Warmly would help eliminate.
- The CRO finds a surprise in her message - an explanation of how Warmly eliminates revenue leaks, a topic they had recently read up on. The CRO clicks on a link in the email, arrives on the Warmly homepage, and reads case studies about how Warmly solved revenue leaks with SaaS Co's competitors.
The orchestration system automatically generated these experiences immediately after that initial call. AI carefully selected the message, buying committee members, and channels based on the surrounding context and historical data.
In the past, such an analysis and outreach would have taken hours. This took minutes. Plus, the call recording was synced to the CRM, transcribed, and processed alongside all other relevant data collected on the account.
So, onto that all-important buying committee meeting. What do you know? Warmly is top of mind.
The marketing manager reaches out to Warmly's AE to schedule another call with the VP of Marketing, CRO, and Sales. The AI, always doing more, includes the CFO on the call because they're deemed vital.
And in less than two days (there could be just 24 hours between the initial website visit and that buying committee meeting), you've got a prospect ready to buy.
Scale
A similar story plays out a hundred more times during the working day as companies visit the site, are qualified in or out, and the orchestration platform delivers the right experience. A single rep can only handle one account at a time, but an orchestration platform can simultaneously service every single account at every stage of the buyer journey.
The previous example discussed a possible experience delivered to the account if they were in-market.
What about those that aren't in-market?
They receive demand-creation experiences, like display ads or personalized emails that route to educational blog pages or videos.
When the target accounts finally enter the "buying window," Warmly's content has already shaped their opinions. The account is primed, and we move to demand capture involving the sales team.
The target accounts arrive on Warmly's landing page, the AI qualifies them as in, notifies the rep when a human needs to be in the loop, and the cycle repeats.
Flexibility
The best AI-powered revenue orchestration solutions give GTM teams the flexibility they need to plug into their existing tech stack and coordinate sales and marketing activities.
That’s not the case across the board, though.
Right now, we’re seeing a consolidation of the GTM tech market.
Salesloft bought Drift. HubSpot bought Clearbit. Leedfeeder merged with Echobot to become Dealfront.
You’re also seeing tools like Apollo.io and ZoomInfo build out unified GTM suites in-house.
Others, like Warmly, are more platform-agnostic. They focus on integrating with a wide variety of tools so you can plug into the tech stack you’re already set up with and orchestrate effective GTM campaigns powered by AI.
Zach Howland, a sales tech stack expert with a ton of experience implementing CRM and sales tools, has a great point on this:
"Flexibility is enhanced utility. The market needs to be more nimble for the coming scramble to modernize sales technology as AI becomes more robust.”
Consistency
Take this example.
Based on data in the orchestration platform, the leadership team finds they're losing deals based on price to competitors, specifically to companies in B2B SaaS at the Series A stage.
So, the team tweaks the orchestration platform to show 20% discounts to in-market B2B SaaS accounts at the Series A stage. The AI also integrates this promotion into the company's messaging while keeping the price the same for all other prospects.
Normally, this type of change would take multiple training sessions with SDRs, as reps leave, are onboarded, or return from vacation. In the past, reps might have tested messaging and pricing on their own.
Now, everything is standardized. This change is implemented immediately and fed through the platform.
Personalization
The other problem with those stock standard sales conversations that lack context?
They’re exactly the opposite of what today’s buyers say they want.
86% say personalization plays a major role in their purchasing decision.
For many companies, especially SMBs, personalization is a great concept but can be difficult to achieve.
Most businesses add a dynamic name section to their email chains and call it a day. As if their name is what customers are talking about when they say they want personalized buying experiences.
A quality revenue orchestration platform provides companies access to the tools they need to deliver personalized experiences.
Again, it starts with quality data (you can’t personalize anything if you don’t know a thing about the person you’re speaking to), coordinated using a combination of AI and automation to identify opportunities to personalize aspects of the conversation.
It's not just about showing that you know their company's name or their role. Revenue orchestration can go as far as customizing the marketing messaging and even the sales assets that customers receive based entirely on the demographic and intent data you have on them.
Adaptive Systems and their Multiplier Effect
When the whole go-to-market functions of demand creation (marketing) and demand capture (sales) play together harmoniously and the experience is delivered correctly, buyers are happy because they feel like it's being done for them, not to them.
When data no longer lives in siloes and is combined to create derived insights that feed back into the platform, the system continuously delivers better experiences to each account.
Advancements in AI, like vector embeddings, can extend LLMs to have long-term memory for the surrounding historical context and experiences delivered to not just one account but every account being tracked in the CRM. This allows the system to create highly customized experiences that extend across the life cycle of the buyer's journey. Like Amazon and Netflix, millions of buyers don't receive templated emails; they receive carefully selected personalized experiences.
The Non-linear Nature of B2B Purchasing
B2B buying doesn’t play out in any kind of predictable, linear order. Instead, buyers engage in what one might call “looping” across a typical B2B purchase, revisiting (for example) six buying jobs at least once.
There's a multiplier effect when all the pieces work together and adapt in real time to the ever-evolving ecosystem of B2B buying.
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Redefining the Role of Human Interaction
Go-to-market teams have already been downsizing and learning to be just as effective with fewer headcounts.
It's gotten so difficult to get someone on the phone that when they finally pick up, after 100 dials, we end up word vomiting just to have them hang up again. It's a horrible experience for both the buyer and the seller.
In the very near future, sellers will move further away from these manual, repetitive tasks because of the increased sophistication, efficiency, and effectiveness of these new adaptive systems. SDRs and AEs can get back to focusing on solving complex customer problems and building long-term relationships. And marketers can spend more time building empathy for the people they are seeking to serve.
And because AI has become quite good at synthesizing data into something humans can understand, we can drill down into the system and reveal important answers to questions like: Who is our ICP? Where are the bottlenecks? Why did we deliver certain experiences? What's been working or not working? Why?
That's the magic of AI-supported revenue orchestration. It gives us the power to be more creative and strategic.
We do what we do best, and leave the rest to automation.
Read on for Part IV on Warmly: The Signal-Based Revenue Orchestration Platform.
Interested to see Warmly in action? Book a demo.