Don’t Expect Immediate Results with AI
Although artificial intelligence (AI) might be overhyped at the moment, in the long run, marketing will be able to derive benefits from it, Forrester Research concluded in a recent report.
AI’s greatest potential lies in data and analytics, with the report pointing out that AI can quickly and easily make sense of large quantities of data and derive insights that marketers can then use for dynamic personalization and content optimization, among other processes.
Additionally, marketing technology equipped with AI can ingest data and customer context from multiple systems, deploy self-learning models that go beyond static predictions, and activate brand interactions across touchpoints.
“Like for many disruptive technologies, marketers overestimate what they can achieve in the short term—one to two years—and underestimate the impact in the long term—five to 10 years,” says Thomas Husson, vice president and principal analyst serving CMO professionals at Forrester and author of the report.
Husson goes on to say that it’s best for marketers to start early with AI technology, despite not seeing immediate results. “AI…takes time and a very iterative approach, and you need a lot of data to train the machine, so the earlier you start, the better,” he explains. “Also, to invest more resources on data engineers and data scientists, you need to have proof points that AI is effective at achieving the marketing objectives you pursue. Starting early is a way to measure the results and make step-by-step progress to justify the business case and investment.”
But while the real-world ROI is slow to come, it does happen. In fact, Husson identified a few companies that have already incorporated AI into their marketing strategies with some positive results. French appliance and electronics retailer Fnac Darty, for example, uses an AI-powered propensity-to-buy model to improve the targeting of its campaigns and reach out to people who are more likely to buy its products. Chinese e-commerce giant Alibaba is another, using an AI-powered chatbot on its online shopping website. In Alibaba’s case, the AI is “well executed” and “helps consumers get faster answers to their queries and increases satisfaction,” Husson says.
The report also asserts that AI will enhance and transform the four Ps of marketing: product, price, place, and promotion. “Indeed, the four Ps are an old marketing framework…but there are basic marketing practices, such as pricing, that will be optimized by AI,” it says.
On the product side, the report cites Netflix and Spotify as examples. More specifically, these two online entertainment companies provide personalized customer experiences by leveraging AI to deliver relevant media recommendations to users. The report also notes that in the world of fashion, Tommy Hilfiger and start-up Stitch Fix are using AI algorithms to iterate products faster.
For price, the report cites Uber as an example: The company uses AI algorithms to optimize pricing based on context and customer data. The report also notes that AI is essential to testing price elasticity and dynamically adapting prices to specific customer microsegments.
When it comes to place, the report states that campaign targeting and real-time bidding on digital ads are some of the most mature marketing applications of AI. Since 2016, Volkswagen has been testing display, search, and social advertising with algorithm-based recommendations for all media buying in Germany, the report says. It does so with the help of Blackwood Seven, an agency that utilizes AI and predictive analytics to forecast spending decisions.
For promotion, the report says that AI can identify a multitude of scenarios and use many parameters to optimize promotions in real time and in context. A company like Groupon, for example, could optimize its offerings in real time and in context by using AI-powered algorithms to determine how customers react to specific promotions at specific moments in time across geographies. Additionally, the report expects that AI-driven optimization will replace traditional A/B testing.
AI got another shot in the arm in an unrelated report from marketing technologies firm Return Path and research firm the Relevancy Group, which found that email marketers using AI saw better results in areas like delivery, engagement, order value, and revenue. Email marketers using AI saw a 1 percent higher inbox placement rate and 2 percent higher open rates and click-through rates. Order value for senders using AI was $145, compared to $138 for those not using AI. And those using AI for personalization have monthly email marketing revenue that is 41 percent higher than those relying on human-curated personalization ($10,024 versus $7,095).