Faster time to revenue: a tangible AI benefit we can all get excited about

Experimenting with AI is on the agenda for most marketers. But its often-cited benefits of productivity and efficiency can be hard to equate against real business value. Here, John Watkins (chief operating officer, Acxiom) explores how AI can make marketing more nimble by reducing campaign life cycles, with the measurable benefit of cutting time to revenue.

Progress in artificial intelligence (AI) is reaching a point where achieving faster time to anything requires effective use of AI solutions. According to the latest McKinsey report, 55% of organizations are already using AI in at least one business function, and the emergence of generative AI is accelerating adoption.

Discussions around the benefits of AI tend to focus on efficiency and productivity. At Acxiom, for instance, we see productivity increase by anywhere from 20% to 80% when we use AI to boost our development capabilities. Projects that would previously have taken months can now be delivering results for our customers in just a couple of weeks.

But the efficiency and productivity benefits of AI aren’t always that easy to quantify, especially in marketing. It can be hard to make the case for the vague concept that AI makes your marketing faster and more productive. So, how about the idea that AI can reduce campaign life cycles so they can deliver revenue more quickly? The promise of cutting time to revenue by 50, 60, or even 70%? Now that’s something any marketer can get excited about.

As long as you have the right data foundation in place, AI delivers faster time to customer understanding, which enables faster time to personalization, which in turn means faster time to revenue. Let’s take a closer look at these three stages.

1. Faster time to customer understanding

Using AI to reduce the lifecycle of a campaign, and make sure it drives revenue more quickly, starts with audience selection. I recently spoke with a brand that took – on average – seven days to select the audiences for their campaigns. By implementing AI, they were able to reduce this process to just minutes, dramatically increasing efficiency.

Once marketers have selected audiences for a campaign, they can also use AI to gain a better understanding of what those customers want and what their preferences are. How and when do customers interact with the brand? Are they more likely to open a marketing email at 10am on a Saturday as they relax over a late breakfast, or at 6am on a Monday as they gear up for the week ahead? Is email the right channel or do they prefer interactions via social platforms?

2. Faster time to personalization

Equipped with in-depth audience understanding, marketers can use AI to quickly personalize the customer experience. This personalization can take place at all stages of the customer journey, from initial exposure to advertising, right through to post-sales support and customer service.

Where brands used to design 20 creative variations for a campaign, AI now allows them to generate thousands of granular variations almost instantly, delivering advertising that is based on real-time insight and is highly personalized to the customer. As someone that enjoys the great outdoors, for example, I’m far more likely to engage with an ad for a brand that’s geared towards something that interests me, like fly fishing, rather than home decor and accessories.

This personalized experience can be carried through to the brand’s website. To continue with the fly fishing example, AI could be used to adapt the homepage so it greets me with reviews of wading gear, or relevant offers on rods and reels. And, once I’ve bought a pair of waders, AI can use that information, along with additional data, to predict what I’m likely to need next time I interact with the brand. Whether that interaction happens via the website or the customer service team, the brand can meet my needs more speedily.

Personalization may not sound like a new approach in marketing, but with the loss of cookies and other third-party identifiers, it’s becoming more complex. By ethically leveraging behavioral patterns and individual characteristics to predict what customers might do or want next, AI takes personalization to the next level and allows the automation of marketing interactions that anticipate customer needs.

As well as improving the customer experience, this automation will inevitably reduce costs by reducing human interaction (though human oversight of AI will remain critical). In fact, in the McKinsey report referenced earlier, marketing and sales functions were among the most likely to report double digit cost reduction from the use of AI, along with functions such as risk and service operations.

3. Faster time to revenue

In addition to speeding up the planning and execution of campaigns, AI allows brands to shorten the purchase path by enabling experiences that make customers more likely to respond, interact, and ultimately purchase.

Our latest research, Where Marketing and AI Collide, reveals almost half (47%) of consumers are more likely to engage with an ad or a marketing email if it contains personalized content, including tailored offers. And over half say personalized ads and recommendations help them find relevant products and services more easily, which ultimately shortens the purchase journey.

But the same report reveals only 12% of brands are actively predicting customer needs using AI at the current time, so there’s plenty of opportunity for further adoption. AI-driven experiences don’t just drive quick sales, they also increase brand loyalty, allowing brands to increase market share and enjoy recurring customer revenue.

A note of caution

When it’s done right, AI has the power to enable greater audience understanding, supercharge personalization, and cut time to revenue. But to function effectively, any AI solution needs a strong foundation of data that is clean, connected, consistent, and compliant. The phrase “garbage in, garbage out” has never been more relevant.

What’s more, marketers that experiment with AI need to consider end-to-end customer journey flows and how each touchpoint will be impacted. The use of AI to select audiences, deliver a fantastic experience, and drive a peak in orders is pointless if a downstream supply chain issue means customers don’t receive those orders on time. A customer's view of a brand is only as good as their last interaction, so when a delightful marketing experience is followed by a poor fulfillment experience it will be the latter they remember. In a fickle and competitive market it’s all too easy for them to take their business elsewhere.

Embracing the art of the possible

AI has the potential to help marketers cut campaign lifecycles, minimize costs, increase brand loyalty, capture market share and realize recurring and new customer revenue in a timelier manner. As long as marketers start with a strong data foundation, and consider all touches along the customer journey flow, AI can drive marketing efficiency and productivity in a way that’s simple to understand – by reducing time to revenue.