But as usual, it's the burning question behind the news that grabs my attention: can AI bridge that persistent sales and marketing gap?
In a video pre-brief, I took that question directly to Oracle. Though I need to see how this plays out for customers, the answers I heard were definitely worth the analysis.
There is another question in play, and that's where Oracle Live started, via a discussion with Oracle's Rob Tarkoff and Larry Ellison on the future of CRM. Tarkoff, EVP and GM, Oracle Advertising and Customer Experience, asked Ellison the question which brings this all to a head: "Where you see the state of CRM today, and why it has failed to live up to its promise?"
Larry Ellison - Sales automation solutions don't automate selling
In his answer, Ellison took us back to the Siebel days, where a central goal of CRM was really "sales automation." As Ellison sees it, that core CRM goal hasn't changed - but it hasn't worked, either:
[Sales automation] doesn't automate selling. It's that simple.
Ellison believes current "sales automation" solutions are really tools for sales management. The problem? They don't help your salespeople sell more. He continues:
The sales automation system has value. It keeps track of your opportunities, keeps track of your contacts. It allows you to communicate with management and say, 'I expect these deals to close in the quarter.' It's really a management tool for individual salespeople and their bosses to make estimates: how many deals will close in the quarter, and figure out what revenues will look like in the quarter.
Now, that has value. But the sales system does not increase sales. It doesn't automate sales. It automates sales, forecasting and improves communication. But what we want to do is actually build systems that help you sell more.
But there's a catch: to pull this off, marketing must be involved. Especially when you consider, as per Oracle: today's enterprise buyer spends 80% of their deal time running their own research and team evaluation - and only 20% engaging with the sales team directly. Enter Oracle Fusion Marketing, says Ellison:
We realized we couldn't do just a second generation sales automation system. To help you sell more, we had to also include the precursor itself, which is marketing to generate - and most importantly - qualify leads. Creating leads is easy. You can get lots and lots and lots of leads. The question is being able to figure out which of those leads are high quality.
Which of those leads do you want to turn over to salespeople, and then get them engaged? So we thought we had a two step process. We had to automate lead generation and qualification, [with] a new second generation marketing system. And then as soon as we got that done, build a second generation sales automation system that would make the salespeople more productive, and help them sell more.
Which brings us to the Fusion Marketing news, and one more element: the role of AI. As per the press release: "The AI engine in Fusion Marketing predicts when customers are ready to talk to a salesperson and automatically generates a qualified sales opportunity in any CRM system." In terms of availability, Fusion Marketing is set to be released in 2022, and is perhaps best described as "campaign orchestration middleware," as per reporter Don Fluckinger. Technically, Fusion Marketing is part of Oracle Advertising and CX, but it should not be confused with Oracle's Marketing, which is where Oracle's prior marketing acquisitions have been applied.
Behind the Fusion Marketing launch - how AI fits in
But is AI really the key to closing that sales and marketing gap? I'm a hard sell on that front. In my pre-brief, Oracle's Holly Simmons and Katrina Gosek had the wonderful opportunity to field my pesky AI questions. I've had clients that solved the marketing-sales gap quite simply: by handing the sales team top shelf, qualified leads. But as the years went on, I've had to face facts: these were (relatively) small clients. The solutions I've seen probably wouldn't scale.
Simmons, who is Oracle's VP of CX Product Management, fleshed out the challenges. When the sales team needs a quick/effective/targeted campaign, good luck:
The marketing team struggles to do that, because most of the demand generation is focused on large scale campaigns, where you're leveraging integrated marketing programs. You've got lots of people involved. It takes time to build those campaigns, and it takes time to develop and deliver them.
Simmons says a key goal of Fusion Marketing is: automate lead generation and qualification. And: make it simple for marketing teams to generate campaigns quickly, without "super-user" capabilities:
People who aren't super-detailed campaign generation super-user types can create and run campaigns to targeted audiences.
So you start with a templated approach to identifying/segmenting the audience, finding the audience you want to target, then being able to build the campaign, again, with a templated, kind of a wizard approach. You build the campaign layer in content that is personalized based on the audience. So it would only show content specific to that industry, for example, so that the salesperson or the marketing person can basically just click it, select it, and [the system] inserts it.
The Oracle team showed me a few screens. I thought this one did the best job of illustrating the process flow, from ad to "conversational opportunity":
The role of AI in Fusion Marketing reflects Oracle's experience with customers, who want pre-built capabilities to make this process easier. Examples of AI-infused features include:
- subject line optimization - to surface the best subject lines
- automated campaign management - and content recommendations
- identifying next best opportunities, or next best actions
- automated lead scoring
My take - can AI bridge the sales and marketing gap?
In both my briefing and the Oracle Live event, Oracle didn't ignore the need to integrate Fusion Marketing with other products - Oracle or not. In addition to Oracle Sales, mentions of integrations with Salesforce and Microsoft Dynamics were also noted. This should be common practice for all enterprise vendors; customers live in a heterogeneous world.
Put aside the semantics on how "intelligent" a solution should be. Instead, let's consider how anything under a broad "AI" semantic umbrella, from automation to predictive actions, can benefit customers. Automating campaign creation, pre-populating with the best content, providing campaign templates, recommending next best actions for busy salespeople - no argument with any of this.
I did have questions, however, on automated lead scoring. Here, I believe subjective considerations are critical. Especially in B2B sales, project leads turn on a dime: rumors of a CIO's departure, a pending merger, a surprise hyperscaler selection, a new inclusion on a short list. Only the best/embedded salespeople have their ears to the ground and anticipate these things. Yes, automated lead scoring is broadly useful, but I believe "AI" will miss things only a human could know. Missing out on a monster new account isn't an acceptable tradeoff for automation.
When I raised that objection with Simmons and Gosek, they explained that in Oracle Fusion Marketing, you can adjust the lead scoring factors (e.g. thresholds) used by the AI engine. So, for example, you could have the system flag any potential six figure sales deal as a priority lead for sales to act on. In other words, there are ways to tweak the system to better incorporate the insights of an on-the-ground team. That makes sense, but I'd still flag "automated lead scoring" as one area where humans will need to cross-check into accounts.
Another thing I heard several times: an automated system can recommend the right content, to enforce brand consistency. That's probably true, and I won't completely dismiss the virtues of consistent brand messaging, but in my opinion, marketing has a more important priority: serving up exceptional/relevant B2B content, at each stage in the customer's unpredictable, or if not unpredictable, then non-linear journey. That doesn't happen nearly as often as marketers think.
I believe marketing is still too obsessed with their management and analytics tools. They aren't good enough at producing content that is indispensable to enterprise buyers. But then again, I hold the still-radical view that B2B marketers must become journalists/editors, and B2B salespeople must become expert advisors, so take that with a grain of salt.
Actually, Oracle anticipated some of my "expert advisor" stump speech, via Fusion Marketing's goal of providing salespeople, and their prospects, with the right info at the right time. In 2022, I'll look forward to digging into customer use case(s) to see how this is working out in the field. For now, Oracle did include a video interview with early Fusion Marketing customer Aon as part of Oracle Live.
So can AI bridge the sales and marketing gap? There's one more hurdle left: adoption. Marketers love playing with new tools, so they aren't the issue here. Salespeople, on the other hand, are notoriously stubborn to adopt. Oracle thinks it can solve this by providing sales with valuable historical information "at their fingertips."
In other words, push info the sales team needs at that particular moment, for that particular prospect. Yes, that could spur adoption. If Oracle Fusion Marketing can live up to Ellison's goal of putting more qualified leads in play, I don't think you'll have an adoption problem.
If and when marketing serves up all the qualified leads sales can handle, you won't hear a peep about a marketing and sales gap. Whether AI can do that at scale is an open question, but it's a great storyline to follow into 2022.