AI’s potential impact on marketing, sales and revenue generation is undeniably huge but not without its limitations.

“Our technology, our machines, is part of our humanity. We created them to extend ourselves, and that is what is unique about human beings.”
Ray Kurzweil, Computer scientist and author

When it comes to marketing, sales and revenue generation, questions on optimising AI abound. Questions such as:

How can we untap the goldmine that is our unstructured data?
What do we need to do to personalise at scale?
Is AI really the silver bullet that we think it is?

James Mollard, Strategy & Growth Director for JPC, shares his insights about the real value of AI for enterprise marketing and sales.

Undeniably there’s a lot of hype. At JPC, we want to cut through the noise, to help you understand what AI really means and exactly how you can harness it to best drive revenue and improve your results.

Today, AI is transforming business. It has enormously exciting implications for the way companies manage their marketing, sales and revenue generation, for example:

Harvard Business Review found that companies using AI tools when making sales calls increased lead generation by 50%¹
Not only that, call times by sales reps using AI were reduced by up to 70%¹
Salesforce’s ‘State of Sales’ report reveals that 37% of professionals say that AI is entirely revolutionising their roles and responsibilities²

But what exactly IS AI, and how can it help us generate more demand, faster?

Definitively AI

Artificial Intelligence (AI) is the capacity of computers and other machines to exhibit or simulate intelligent behaviour. This includes a wide spectrum of capabilities such as visual perception, speech recognition, decision-making, and language translation deployed to accomplish tasks typically requiring human-like cognitive processes. But this rather prosaic definition fails to convey the innovative ways that we can leverage AI for business benefits.

What does this really mean in practical terms and how can we apply it meaningfully to drive enterprise sales and marketing? And despite the clear advantages it brings, can it really replace the creativity and human connection at the core of our sales and marketing activities?

When it comes to enterprise marketing and sales, we can identify some of the key benefits that AI brings as:

1. Extracting value from unstructured data

Due to the enormous scale and complex distribution of data across organisations, every enterprise is sitting on an untapped data goldmine. AI can rapidly synthesise vast amounts of fractured, disorganised data into structured formats suitable for analysis. Machines taught to work across complex, matrixed environments can mine and manipulate data previously too overwhelming for a human or even for a programmed solution.

For example, many of us are familiar with Alexa or Google Home – physical IoT devices that collect information about our surroundings and send sensitive sensor data back to the cloud. These offer perfect examples of unstructured data which can harness the power of AI to extract valuable digital insight. When we consider that – according to Deloitte – only 18% of companies have efficiently extracted value from this uncharted territory, then the untapped potential of AI is clear.³

2. Personalising at scale

You’re probably aware of the potential in generating language and images through deep learning models like Midjourney, ChatGPT and Pika. However, most of the outputs today are a result of human prompts (many prompt engineering guides are easily accessible on LinkedIn?!) and so are difficult to scale.

Using Large Language Models to interpret the campaign analytics from marketing automation, and adapt responsive messaging and visuals ‘on the fly,’ in theory enables unique levels of personalisation and suggests the possibility for 1-2-many ABM that actually looks like ABM. But, in fact, the true value here comes from the automation of manual tasks – enabled by AI – that frees up actual humans to maximise their strategic time. Man and machine in perfect harmony.

3. Optimising bid response

If you’re an enterprise B2B tech, managed service, construction or other service provider business, then it’s likely much of your new (and recurring) revenues will come as a result of a formal bid process.

You’ll also know that formal tendering is labour intensive and time consuming. And you probably won’t be surprised to learn that >45% of the intellectual capital invested is simply re-authoring what’s already been written. Natural language processing can analyse historical responses and extract and reconfigure relevant content, while reinforcement learning trains the model to keep rewriting the response. Eventually the score is fully optimised for each answer.

But – and there is most definitely a but –

Despite its undoubted promise, AI still has some very real limitations when it comes to fully optimising marketing and sales, most critically:

1. Product complexity

Out-of-the-box NLP (Natural Language Processing) has a hard time thoroughly grasping intricate product portfolios and technical environments purely from publicly accessible data.

2. Strategy sophistication

Highly-personalised strategic guidance on target business and stakeholder imperatives, personas and value propositions requires sophisticated human context and craft. AI recommendations alone are often too generic or simplistic.

3. Data bias

AI can only generate results from the finite input it receives. Human bias – conscious or otherwise – skews data and targeting, leading to inaccurate predictions and reduced diversity in campaigns. Bias can stem from unrepresentative or prejudiced training data, which reinforces inequalities within the data and can potentially damage the efficacy of the output.

To counteract bias, we need to use diverse datasets, monitor AI for fairness and follow ethics guidelines. Involving teams with varied backgrounds and perspectives can also help identify and correct biases, ensuring equitable and effective marketing strategies.

AI is not a silver bullet

Automation can undoubtably be a force for good business, but it still needs that human edge.

Its greatest value comes from enhancing human creativity, strategy and industry expertise. Purpose-built AI – expressly trained on an organisation’s unique offerings, customers and challenges – shows us the most concrete value.

If, as marketing and sales leaders, we can identify the pain points that will benefit most from automation support – while we double down on the irreplaceable human elements that build relationships and drive complex decision-making and strategic planning – then irrefutably AI can streamline revenue operations and create competitive advantage in Enterprise B2B.

At JPC, we’re developing a number of routes for AI to do exactly that.

We’re looking for co-creation opportunities with organisations in the tech, telco, construction and professional services sectors. So, if you’re keen to explore how strategy and AI combine to create sustainable growth, we’d love to talk to you. Please get in touch.

Dhanashree and Sucheth (2024) Unstructured Data Extraction Made Easy: A how-to guide, Nanonets Intelligent Automation, and Business Process AI Blog. Available at: https://nanonets.com/blog/unstructured-data-extraction/