The new year means it’s time for all the terrible “I haven’t seen you since last year!” jokes and making those soon-to-be-forgotten resolutions—and of course, predictions posts! Or you can just lament that it’s too soon to talk about 2019, and try your absolute best to avoid all the new year cheer.
While your chosen level of new year-denial is a personal choice, if you’re a marketer, taking advantage of machine learning (ML) powered technologies probably won’t be in the coming years. Invoca customers like performance marketing agency Visiqua are using our Signal AI technology to analyze inbound customer phone calls not only to disposition calls in real time, but to use its predictive analytics to optimize marketing campaigns, reduce acquisition costs, and better serve their customers. You can read their case study here.
How can you use ML in 2019 to make yourself a better marketer? The Think with Google blog offers some great food for bot-thought in this piece on how marketers can use ML to drive growth:
Stop reacting. Start predicting
Successful business performance today relies on brands being able to predict what customers might need at every stage of their purchase journey. By harnessing the power of machine learning and automation, brands can do just that.
Organizations with incentives to use machine learning are able to move away from old-fashioned retrospective or reactive KPIs and make smarter decisions with forward-looking and predictive performance goals. That’s because with machine learning technology, KPIs no longer have to be analytic outputs, but rather data inputs that help train algorithms to anticipate opportunities for growth.
Shiseido is one brand that knows driving growth means not only delivering on people’s stated needs (like replacing a daily moisturizer) but also in predicting intentions. “People can’t tell you exactly what they might want next, so we take cues from past actions to predict future intentions,” said Global Chief Digital Officer, Alessio Rossi. The beauty brand gleans critical insights through tools, such as its BareMinerals Made-2-Fit app. Then, using machine learning algorithms, it’s able to make truly personalized recommendations for complementary products that the customer might not think to try.
Make your marketing count
Our research shows that marketing leaders are more than twice as likely as their mainstream counterparts to agree that their organization is already investing in automation and machine learning technologies to drive marketing activities. When these marketing activities are linked to business goals, we see a significant upward growth trend.
In 2017, for example, when HomeAway started using machine learning and automation to activate customer segmentation based on real-time signals and behaviors, it saw a 46% increase in gross bookings and a 115% increase in revenue year over year. “One thing automation has helped us get right is who sees our ads,” said David Baekholm, SVP of growth marketing. “We’ve not only become better at finding the right customers, we’re now also really good at not spending on the wrong customers.”
Get a more holistic view of your customers
Business success today relies on your ability to have a current and integrated view of your customers — only then can you develop meaningful relationships with them and deliver long-term brand growth. Our research, found that organizations with incentives to use machine learning also have KPIs that help them develop an integrated view of their customers.3
Retailer 1-800-Flowers is one of the brands leading the field in this area. The brand relies on machine learning and automation to help it learn about its customers and deliver personalized experiences. CMO Amit Shah, who was interviewed as part of the research, believes that getting in early has given the brand a real competitive advantage. “I think what we will find, five years down the road, is that the people who took the early bets in artificial intelligence actually achieve the learning that cannot be copied,” he said.
Do more with your data
Companies with incentives to use machine learning have more ability to drill-down and see their KPI data in greater detail. This can lead to increased knowledge sharing and transparency, and help teams work together to make smarter, data-driven decisions that achieve corporate-wide goals. In fact, organizations that are incentivized to use machine learning believe they are better than their competitors at making data-driven decisions.
Kelly Watkins, VP global marketing at Slack, also participated in the research. She recognizes that to stay ahead of the competition she must give her teams the tools they need to make the best decisions. Today, that means automation and machine learning tools. Her intention is to “enable folks in my organization to use their minds to solve strategic problems and to be more consistently looking for insights in the data that can shift the strategy and shift the execution.”