AI in B2B Marketing: Take it to the next level with data

If you follow our insights, you’ll have seen and heard the opinions, advice and recommendations curated by Twogether on the topic of AI for marketing and sales.

As the agency’s Director of Data Operations and Performance, I have been following it all from an ops point of view. For me, it’s all about the data.

Go from generating leads to predicting profit

The potential of AI to increase revenue and profits is huge, especially if you allow data to take the lead.

AI provides incredible capabilities, but in reality, AI is only as good as the data it’s fed. For an organisation to truly embrace the possibilities that AI provides, it’s critical to look at your existing infrastructure and how aligned your data is. The more complete data you feed in, the better your results will be.

As an example;

If you are only able to provide data from your paid media activity, the recommendations AI can provide will be limited to that as its source, and therefore what can be achieved.

In your role as a marketing leader, you may start out asking a broad question like:

How can we generate more leads?

Your AI platform would be able to identify that from the data you’ve provided, content syndication platforms and LinkedIn lead gen forms are your biggest lead sources. It’s clear from this limited data – pay more, get more leads. Since that’s all that has been input to AI.

You may want to get more granular, and ask: “How can we generate more leads with a similar budget?” AI might give you the same response as above but recommend that you only use media partners that have a low(er) cost per lead (CPL).

You already know this. What you really need are higher-quality leads. And, although your target may be leads, what your leadership want is revenue. AI can only work with the data you feed it, and without an additional layer of data you can't expect AI to be able to tell that story. Isolated data = isolated analysis.

The possibilities of enabling AI with multiple data sources

Now here’s where the potential of AI really kicks in. Let’s take this a step further.

Imagine if you took the time to add sales data into the mix (tracking leads all the way to close). Now, instead of simply asking how to generate more leads, you’re able to ask more complex questions to drive marketing’s impact.

Something like: “We need to increase company sales by 20% and profit by 30% this year. Where should we invest our marketing budget to achieve these goals?”

When fed the right sales data, your AI tool will be able to analyse historical sales results and identify where marketing had the biggest impact on them, in a matter of seconds. It could even output the information in a way your leadership will understand. It could identify existing customers with good potential for up-sell or cross-sell activity, as well as forecast the potential in bottom line to your business.

Or those that have purchased high-profit-margin products. It would be able to take these findings and use them to find look-a-like audiences using your media partners. Target these with the right message and you can be reasonably confident that your spend will generate revenue and profit.

Your AI tool could give you:

• A clear list of target accounts that already know your brand and that are most likely to purchase
• A list of accounts that meet similar criteria, who don’t know you, but who you can target with a dedicated demand generation strategy, that is complimented with brand awareness activities to increase conversion potential
• A breakdown of how best to split your budget across these audiences
  
  

It’s all about the quality of your data

AI is great, and it can deliver helpful short-term benefits. But to get the most out of it, you need to think strategically. And you need to feed it high-quality, integrated, and well-structured data that it can use to generate trust-worthy strategic insights.

Ready to unlock the strategic benefits of AI for B2B marketing?

As a global B2B tech marketing agency, our data and ops experts lead the charge when it comes to collecting, connecting and analysing marketing performance data.

This is just one of the use cases for AI in marketing and sales, but if it’s something you’d like to explore, let me know. We’re always up for a data-driven discussion.

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