Unlocking AI’s potential in B2B marketing

Unlocking AI’s potential in B2B marketing

]

As predictable as the sun coming up in the morning, each day I speak with sales and marketing leaders who fear they’re not doing enough with AI and have fallen too far behind.

They feel unsuccessful and worried they aren’t meeting leadership expectations. Take a deep breath. You’re not an anomalous failure, and it doesn’t mean your team sucks.

I just read a post the other day that talked about the “early days” of AI. The writer was referring to last fall and winter. While it sounds odd, it’s becoming clearer how these tools are meant to work with you and your team.

Enough of the ‘current state’

About 87% of businesses are in the early stages of AI adoption or have not yet started, according to McKinsey. Gartner indicates that only 24% of marketers report having AI and machine learning as a top priority in their tools and tech stack, highlighting a significant gap in prioritizing AI as a portion of their budgets.

Is AI a silver bullet? Do you have highly proficient AI experts on your team? Can you afford one of the international consulting organizations to drive an eight-figure project for you? Probably not.

Do you need all those things today? Probably not. However, it’s potentially transformational for those who invest in a forward path.

What does a successful ‘future state’ look like?

The plan: ‘By failing to prepare, you are preparing to fail.’

Benjamin Franklin had this right nearly 300 years ago.

Do you have a cross-functional team to evaluate use cases and create a policy? AI is not unlike every other part of an organization; you need to prepare and have a plan. Without this plan, you’ll end up with Bring Your Own AI (BYOAI) and chaos. AI is happening already.

We recommend that clients create a panel of interested parties with various interests. While you need to have voices from your technical, HR and legal teams, you must surround these protectionist voices with parties interested in creating value, such as sales, marketing, customer success, sales enablement, product and more.

The interests of data privacy, responsible use and careful selection of use cases are important and should be advocated. However, these concerns should not be the only focus, as they might not fully understand your goals and could end up hindering progress. They need your insights and education.

Dig deeper: A people-friendly approach to adopting AI in marketing

The need: Identify practical use cases for your team

Narrow down your aperture of consideration and avoid confusion and consternation. You’re not trying to carve this decision into granite, but take a moment to find applications your team will find valuable. In this decision process, consider selecting an area where you have low perceived risk and high perceived value.

Many marketers choose content creation and personalization versioning for this exact reason. It’s hard to do well, and the result is that one would hope this information becomes public: IT, privacy and legal teams would (should) have no concern over this use case and others where the cultivation of information is innocuous.

The goal: Effectiveness

When you select use cases, consider how AI can help make your team more effective. Generative AI is amazing at assimilating hundreds of dimensions of analysis simultaneously. The average super-smart person can analyze two to three dimensions. This is its key strength: effectiveness. AI inherently creates efficiency, so the desired future state is to create productivity (effectiveness + efficiency).

How will you identify the productivity gained for each use case? What measures will focus on effectiveness? Separately, what will measure efficiency? When “experts” focus on efficiency, they’ve got it wrong. Unless you solve the effectiveness part of the equation, efficiency simply doesn’t matter.

Think of it this way: how many times have you read an AI-word-salad email you intuitively know was created faster than a person could have typed, but it utterly lacked any sense of relevance? Hundreds? Yeah, me too. Efficient? Yes. Effective? No. And, doing more of this is negative and corrosive, not positive and of value.

Dig deeper: From efficiency to efficacy: 2024’s B2B marketing revolution

The challenge: Context

For all that large language models know, they’re nearly unusable for sales and marketing use cases. While it can tell you about Quantum Physics or farming best practices in the Sub-Saharan regions of Africa, they completely lack the context of your organization, how your solution approach is better, how your capabilities are superior or why your audience needs may differ from competitors.

The most expensive path is to rely on prompt engineering, upload a few pages of content or create numerous microscopic custom GPTs. This approach is the current state, and we see confusion, low adoption and lack of impact.

Without this context, your interactions are generic, and generic is where the AI word salad begins.

Focus your solution selection on the ability to train the AI tool on your company strategy and perspective. Use prompt engineering to achieve this.

In a non-trivial sense, even doing nothing with AI doesn’t mean you’re not using AI. Your phone and video call transcription services all use AI.

But should you guide the adoption or let it occur randomly? BYOAI is a thing, just as BYOD (Bring Your Own Device) was a thing a decade or two ago. I generally coach organizations to see three classes of AI tools:

Native. While most people will instantly consider chat-based tools like ChatGPT, there are also their enterprise parents, like OpenAI. Many of the “experts” get this wrong. You can create an OpenAI account and access the completely unthrottled environment of OpenAI.

Data privacy and hallucination are largely a byproduct of consumer-oriented chat-based tools, not enterprise counterparts. Trying to make the consumer chatbot act in a business environment is problematic. It’s an enormous time-suck (expensive) and only drives a nominal amount of value because it lacks the context of your business that can drive value.

Direct access to enterprise tools can be more expensive and require new skills, but it is THE way to experience AI.

Embedded. Think about the tools you use every day in marketing and sales — your CRM system, marketing automation platform or sales enablement tools. Embedded AI solutions nestle right in these familiar environments. They bring functionalities like predictive analytics and personalized content recommendations directly to your fingertips.

But let’s be candid. While these solutions streamline repetitive tasks and provide valuable insights, they often lack the unique context of your organization’s specific needs and goals. This shortfall restricts their ability to drive genuine effectiveness.

The pivotal question is: Do these embedded AI solutions enhance the effectiveness of your AI use cases? For instance, do they make your marketing campaigns more targeted and impactful or merely expedite the process without adding substantial value?

Before you use these tools headfirst, evaluate how well they align with your strategic objectives. Are they meeting the nuanced requirements of your marketing and sales efforts or falling short? This self-assessment is crucial in determining whether these embedded options truly drive transformative results.

Purpose-built. These are the bespoke solutions typically focused on a narrow use case. Because they’re tailored to particular use cases, they’re more likely to provide relevant context and actionable insights. But here’s the concern: how well can they adapt to your unique environment?

The key here is to ensure the context you provide is sufficient to drive meaningful effectiveness. Can you train the tools to thoroughly understand your capabilities and solutions, audience, differentiation and market approach?

Dig deeper: It’s time to teach AI about your brand

]

Something went wrong, please try again later.

Invalid email Something went wrong, please try again later.

Sign up to FREE email alerts from BusinessLive - Tech - the very latest innovations, inspiration and business news every Tuesday

Something went wrong, please try again later.

Userled, an artificial intelligence (AI) startup that enables business-to-business (B2B) firms to create “hyper-personalised” marketing campaigns, has secured £4m in pre-seed funding. The platform developed by Userled aims to automate the creation and distribution of highly personalised marketing campaigns across various channels, including email, LinkedIn and Meta.

The funding round was spearheaded by early-stage venture capital fund Localglobe, with contributions from Dig Ventures and a group of angel investors. Founded in 2023 by seasoned entrepreneurs Yann Sarfati and Tristan Saunders, who have tech industry experience from companies like Salesforce and American Express, Userled plans to use the funding to expand its team and continue developing its AI-powered technology.

This technology is already being utilised by companies such as Wayflyer, Deel, Onfido and Encord. Sarfati, co-founder and CEO of Userled, believes there is a demand for tools that simplify and scale personalised marketing.

He stated: “Marketers have to put significant time and resources into manually building personalised campaigns which feel impossible to scale. They lack the tools that should enable them to do this simply and at speed to surpass the impact they can achieve through manual campaigns.”

(Image: Userled)

“Userled breaks this cycle. We’re making personalised marketing easy, accessible and efficient to give B2B companies the competitive advantage they need in today’s ever-shifting digital landscape,” he added.

Userled’s innovative platform operates independently of third-party cookies, utilising its unique Cookieless Fingerprinting and Identity Layer technology to provide marketers with comprehensive insights into customer behaviour at both account and contact levels. The company asserts its compliance with GDPR and CCPA regulations.

Mish Mashkautsan, a partner at Localglobe, commented: “Userled brings the power of generative AI to reshape a complex and mission-critical workflow for marketing teams.”

“By accelerating the creation and distribution of personalised content and capturing contact-level insights without cookies, Userled provides a seamless solution to drive efficient growth a key priority for any B2B company, especially these days,” he further remarked.

AI is widely regarded as a transformative force in the marketing sector, with many advocating for businesses, particularly resource-constrained startups, to leverage its capabilities, as reported by City AM.

A recent Venture Planner survey involving 2,000 emerging entrepreneurs revealed that 78% are open to adopting AI tools to jump-start their ventures.

S4Capital, the digital advertising and marketing services firm established by Sir Martin Sorrell, is also significantly investing in AI technologies to enhance its offerings to clients.

]

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More

Adobe announced the general availability of the B2B version of its Journey Optimizer. This version will let enterprises use generative AI to help them identify and persuade the correct decision-makers for large purchases.

The company said in a press release that sales and marketing teams often have a hard time reaching the right people who make purchasing decisions for software or hardware.

With Adobe Journey Optimizer B2B (AJO B2B), brands can reach the right person and personalize their sales pitch. Adobe told VentureBeat in an email that AJO was first previewed in March.

AJO is built atop Adobe Experience Platform, which Adobe said is “the underlying data layer that provides brands a single view of customers across any channel.” It lets users create buying groups to organize customer information.

Generative AI can recommend missing roles and any missing team members to populate the lists fully. Marketers can then use Adobe’s AI assistant to build out a marketing plan for individuals they’ve identified using the buying group lists they’ve created.

Adobe said it will also add lifecycle capabilities for each group so brands can trigger real-time interactions once milestones—like contract renewals—are reached.

Leveraging AI for custom content and outreach

As Adobe offers AI tools for creative projects, AJO will also let brands bring in AI assets from Adobe Firefly or Adobe Experience Manager to their libraries to create customized templates quickly.

Pricing for AJO is not publicly available as Adobe said it does not “provide specific pricing details for products such as Adobe Journey Optimizer, given that it varies greatly depending on the needs of each customer.”

Adobe has been leaning on AI models and adding the technology to its creative platforms, with the integration of the AI engine Adobe Firefly to its creative suite in September last year.

Since then, the company released even more AI tools to its customers. It launched the AI assistant on the Adobe Experience Platform in June. The latest version of Firefly now includes full capabilities to generate AI images.

Courting controversy

However, the company found itself in hot water after an update to its Terms of Services, which made it seem it would surveil users and train its AI models on content made or touched up using Adobe products. Adobe responded that its policy had existed for years and that it does not look at or train on any material users have on their local servers.

Adding generative AI to marketing tools is not new, with companies like HubSpot including several AI features in its products.

]

Adobe, long a stronghold on the consumer marketing side, released a B2B cloud app that taps generative AI to connect selling teams with buying teams and creates content for different personas.

Journey Optimizer B2B Edition combines data from marketing, CRM and customer data platform (CDP) to personalize enterprise sales pitch content. For example, the vice president at a prospective sales lead’s company will be concerned with different aspects of a product or service than an end user, IT person or finance executive. It also includes marketing performance analytics, dashboards and optimization tools.

Adobe partnered with Microsoft earlier this year to develop an AI assistant for the Adobe Experience Platform, which its bundles customer analytics, CDP and customer journey tools and is a subset of Adobe Experience Cloud, its overall marketing platform. The assistant can identify audiences from marketing and CDP data and then deliver marketing messages across different channels, such as email, calendar and SMS text.

The concern for many enterprises as they evaluate generative AI tools for functions such as these is predicting their costs, said Rebecca Wettemann, founder of Valoir, a tech advisory firm. That formula gets more complicated when factoring in large language model consumption fees.

“The content generation piece is a real pain point for marketers today,” Wettemann said. “The ability to point an intelligent engine at something and say, ‘Create all these different bits of content,’ makes a lot of sense. Do I need Adobe to do that? They’re not the only ones doing it.”

The generative AI tech sector for marketing includes large vendors, such as Salesforce, Google and SAP, but also smaller companies, such as Klaviyo and Jasper. Many of the tools focus on assisting individual marketers with identifying market segments or creating emails, storyboards and other marketing campaign collateral.

Adobe’s B2B marketing tool offers generative AI prompts for CRM and marketing data.

Specifically, Salesforce has invested heavily to commingle AI-generated marketing content and B2B CRM data, as has SAP, Oracle and Microsoft. Users of those products have access to many, or at least some, of the features in Adobe Journey Optimizer B2B edition.

But Wettemann added that Journey Optimizer B2B Edition will appeal to current Adobe users because it could ease the integration of generative AI and Adobe Marketo inbound lead data into their CRM workflows.

Sundeep Parsa, vice president of product for Adobe Experience Cloud, showed the B2B app running inside of Salesforce’s interface and said the company also is targeting users of other CRM apps.

B2B requires many-to-many marketing campaigns as opposed to the one-to-one efforts for consumer products. That’s where generative AI can cut the time to merge customer data from both marketing and CRM systems, Parsa said.

On top of that, CDP data can further personalize campaigns to longtime users of a company’s product because it holds information about product usage, adoption and other data points that aren’t contained in the CRM or marketing systems. Parsa said the typical Adobe CDP user is a large enterprise that deploys multiple CRMs as well as collects data from applications and services outside of CRM or marketing for a more complete customer picture.

Manufacturing and financial services customers will be the most likely early adopters of Journey Optimizer B2B Edition, Parsa said. Those verticals typically have the most advanced data strategies. That’s what it will take to push generative AI into the B2B realm, because it’s far more complicated than B2C.

“We’ve seen some [progress], but by industries: high tech, manufacturing and financial services,” Parsa said. “[That’s] why I believe they are ready to now adopt this new way of nurturing those buying groups.”

Journey Optimizer B2B Edition is a new product that carries its own license and is priced according to the size of the user’s marketing operations.

Don Fluckinger is a senior news writer for TechTarget Editorial. He covers customer experience, digital experience management and end-user computing. Got a tip? Email him.