AI and B2B marketers - friends or foes?

If you’re a marketer, you probably have a big wish list (on top of “bigger budget”, obviously).

What’s on yours?

Improved customer insight generation? Certainly.

Greater personalisation? Definitely.

More planning precision? Absolutely.

An enhanced customer experience? Shut up and take my money!

Depending on where you – and your company – sit from a capability and resourcing perspective, the above items might be described as business as usual, or they may qualify as Big Hairy Audacious Goals.

The good news is – regardless of which end of the curve you currently sit – ticking these items off is about to get a whole lot easier.

Welcome to the party, Artificial Intelligence (AI amongst friends).

Unless you have been on another planet recently, its been hard to avoid the topic of Artificial Intelligence. While ‘AI’ has been a thing for a long, long time, it was really the release of ChatGPT – at the end of November 2022 – that sent the whole world crazy mad for AI.

Before we knew it, everyone was asking ChatGPT to make decisions, write content, even create art.

From a business perspective, there’s already strong evidence to suggest AI can help drive cost reductions AND revenue increases – a combination that will make CEOs and CFOs very happy.

Research by McKinsey released in 2021 – based on a survey of businesses already employing AI – found that AI was particularly strong in driving cost reductions in supply main management, manufacturing, service operations, and strategy & finance.

On the revenue side, around 70% of respondents said that AI had driven strong revenue increases for the sales & marketing and product development functions.

Among B2B marketers, much of the narrative has focused on content creation, as copywriters everywhere became increasingly anxious every time someone published a ‘jobs most likely to be replaced by AI’ article (itself probably written by AI).

Certainly, as with any technological advance, an impact on the workforce is to be expected. But AI promises quite the disruption. A report published by the World Economic Forum in 2020, for example, predicted 85 million jobs will be replaced by AI by the year 2025. Mckinsey’s more conservative 2021 estimate, on the other hand, is 45 million by 2030.

For the record, a recent list of roles impacted did indeed show copywriters and content creators pretty strongly in the top 10, making me feel a tad nervous as I write this!

Top 10 roles to be impacted by AI (source: tech.co)

Personal considerations aside, the opportunities for AI to create value for B2B marketers is immense, not just at the margin, but in fundamentally changing our ability to truly understand our customers and to co-create offerings for them.

Some of the big-ticket items that will be transformed by AI include lead generation and scoring, customer segmentation, customer insights, campaign optimisation, and the personalisation of customer journeys.

As important as all items these are, two that get me particularly excited are those revolving around customer insights and around lead generation.

Lead Generation and Scoring
Generating high-quality leads at scale is one of the biggest challenges faced by B2B marketers today.

Part of the problem lies in the resource intensity of data collection, management, and analysis. Applying AI into lead generation processes can help solve this issue.

AI can bury deep into sales funnels to capture highly accurate, real-time data across channels and databases ordinarily inaccessible to, or overlooked by, humans.

Armed with this improved visibility and data accuracy, marketers can identify more leads, create more granular customer personas, and implement more comprehensive lead scoring systems.

Better quality customer insights
Accurate buyer personas are a critical foundation to a personalised messaging framework that can start from the moment the target enters the sales funnel for the very first time.

Combined with AI, businesses can use social listening and analysis tools to gain a deeper understanding into customers’ pain points, buying behaviours, and who competitors are targeting. This knowledge can help businesses create more accurate personas, allowing them to approach prospects customers with timely, relevant messaging designed to nudge them further along the buying journey.

It’s not quite time for copywriters to retire
To paraphrase Mark Twain, reports of the death of copywriters have been greatly exaggerated. While content creation is an obvious use case for AI, it is currently not without its challenges when it comes to quality, thought leadership content.

There are a few reasons for this.

Content originality and quality
While Large Language Model AI is certainly capable of generating engaging content, it will almost certainly draw on content already existing online, which doesn’t automatically guarantee its accuracy, nor originality.

I experimented myself, asking ChatGPT to draft a cheeky 500 words on some investment topic. The end result was certainly well written, and grammatically correct. But alarmingly, the references it used were actually generic and, on closer inspection, non-existent. These kinds of errors can completely trash your brand reputation, and it goes without saying you should always fact-check and proofread AI-generated content before publishing it online.

And then of course there is the actual quality of that content. Genuine thought leadership relies less on the style and more of the substance, bringing together various strands of research – some of it often quite disparate – and weaving it together in a cohesive narrative from which is drawn an original, and sometimes controversial, conclusion.

This isn’t just my view – Google has something to say about the quality of content too.

For years they have been discouraging poor quality content – regardless of whether its AI or human generated.

What Google says about poor quality content
“Poor quality content isn’t a new challenge for Google Search to deal with. We’ve been tackling poor quality content created both by humans and automation for years. We have existing systems to determine the helpfulness of content. Other systems work to elevate original news reporting. Our systems continue to be regularly improved.

Google’s ranking systems aim to reward original, high-quality content that demonstrates qualities of what we call E-E-A-T: expertise, experience, authoritativeness, and trustworthiness.

Calling out AI generated content
Being able to trust the source of content can be as important as the content itself, and like many, this is an area I am watching with interest. Some of our defences against AI may be AI itself (some universities are already employing AI to detect work created by AI).

Some sort of regulation may also be necessary, and already around the world we are seeing various jurisdictions mandate that certain AI content be clearly identified as such.

Just recently, for example, global creative agency Ogilvy called for policy change by asking the advertising industry to mandate disclosure around the use of AI generated Influencers.

The ‘AI Accountability Act’ proposal is designed to address the rising use of artificial/virtual Influencers by brands by maintaining influencer authenticity transparency when used across social media.

The use of a hashtag declaration #poweredbyAI, combined with a new watermark on AI-generated content, aims to provide clear visual identification, maintaining accountability in disclosing when used as part of influencer campaigns.

Advisor insights – driven by Ensombl’s AI
Here at Ensombl, we jumped on the AI train a while ago. Our proprietary AI engine allows us to dive into the thousands of conversations taking place across our advice community platform and get to the heart of the real issues and challenges that are top of mind for advisors.

These insights then feed into the content we develop with our corporate partners – content designed to solve advisor problems, and which is, in essence, co-created with advisors themselves.

The co-creation dividend: 45% higher engagement
The payoff to marketers using co-created, insight-driven content is significant. We call it the ‘co-creation dividend’ and last time we checked it represented a 45% uplift in content engagement.

You don’t need ChatGPT to tell how impressive that is.

To find out more, drop us a line.

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