Back in 2006, Phil Fernandez, Jon Miller, and David Morandi founded Marketo. At the time, they only had a PowerPoint. But then again, they also had a compelling vision to create a new category known as marketing automation.
Within a few years, Marketo would become one of the fastest software companies in the world, as the market-product fit was near perfect. By 2013, the company went public and then a few years later, it would go private. Then as of 2018, Marketo agreed to sell to Adobe for $4.75 billion.
The deal will certainly be critical to scale growth even more and there will certainly be major synergies. But I also think there will be a supercharging of the AI strategy, which should be transformative for the company.
Yet this is not to imply that Marketo is a laggard with this technology. Keep in mind that the company — in 2016 — launched Predictive Content. The system leverages AI to help marketers offer better targeting based on a prospect’s activities, firmographics, and buying stage.
After this, Marketo created other offerings like:
- Account Profiling, just announced at Adobe Summit, uses a customer’s current customer data to determine the best prospective accounts to target based on billions of data points in real-time.
- Predictive Audiences for Events selects the best audience to invite to an event and then forecasts attendance and recommends adjustments to meet customers’ goals.
But all this is still in the early days. “AI will become pervasive throughout B2B marketing efforts, improving performance and increasing efficiency throughout the entire buyer’s journey,” said Casey Carey, who is the Senior Director of Product Marketing for Marketo Digital Experience at Adobe.
In fact, here are just some of the important capabilities he sees with B2B marketing:
- Audience Selection: “AI can inform improved audience selection and segmentation. Armed with tools to identify a target audience based on past behaviors, marketers can offer tailored experiences that will resonate with potential customers.”
- Offers and Content: “AI can help marketers deliver higher value to potential customers by applying machine learning to the content selection and delivery process. This includes creative, formats, and offers. By creating personalized messages based on previous choices and behavior, marketers are able to engage in ways that resonate every time.”
- Channels: “AI can help marketers determine the best time and place to engage with potential customers based on past channel performance and what you know about the individual.”
- Analysis: “Using AI, marketers can quickly understand what’s working and what’s not so they can make adjustments to improve performance and drive a better return on their investments.”
- Forecasting and Anomaly Detection: “It is not enough to know what to do, but you also need to understand what the impact will most likely be – this is where AI can help. By analyzing past results, AI can predict outcomes like campaign performance, conversion rates, revenue, and customer value. This provides a baseline for planning and then making mid-course adjustments as anomalies occur or other changes are needed.”
Yes, this is quite a lot! But Casey has some spot-on recommendations for marketers on how to use AI. “Rather than trying to understand the technology behind AI solutions, savvy marketers should focus instead on finding opportunities to use them,” he said. “If you catch yourself saying, ‘If only I could figure how to put all this data to use,’ consider an AI application. On the other hand, despite everything that can be achieved by strategically implementing AI, there are still areas where AI solutions are not appropriate, such as situations where there is poor quality or insufficient data. AI is, after all, artificial intelligence. It’s only as good as the data you feed it.”
But AI is not something to ruminate about — rather, it is something that must be acted on. “Two things are happening that are making AI more prevalent in marketing,” said Casey. “First, prospects are expecting more relevant and compelling engagement along their buyer journey, and second, more data is becoming available to inform our marketing strategies. As a result, the historical way of manually analyzing data and using rule-based approaches to marketing are no longer enough.”