One of the biggest challenges that marketers are facing today and struggling with is the massive amount of data that we see in our line of work, day in and day out. Some would like to call it “data overload,” which is only getting compounded due to the speed at which we’re getting data in ever-increasing ways.
I like to say, and I am sure other marketers will agree, whenever we are putting together any strategic plan, we start with the data. We say, “What does the data tell us?”
Data dictates everything that we do, from what people say on social media and review sites about our brands and products to our customers’ suggestions on things that we should consider implementing, like a new soda flavor or a new travel route. Further, there are times when the data that comes to marketers also gives us a kernel of insight into potential consumer trends that may impact our brands and products.
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How can we as marketers embrace and take full advantage of the data that we see every day, and how can we do a better job in consuming and evaluating the data?
Artificial Intelligence (AI) as technology is currently being used throughout marketing and also in advertising. For example, in programmatic advertising, AI is being used to help advertisers and publishers optimize the results they achieve when it comes to automated buying and selling of advertising space. AI is also being used in marketing when speed is essential. AI tools use data and customer profiles to learn how best to communicate with customers and then service them tailored messages at the right time without intervention from marketing team members.
How else can marketers embrace AI to use in their day-to-day work? Here are a few examples:
Using AI to Improve Product Development and Innovation
A brand that is using AI technology to help with products is Nissan. Launched in 2016, Nissan developed DriveSpark to use AI to speed up new vehicle designs and development. A car manufacturer that is also using AI technology to help with product development is Jaguar Land Rover. The company sees the value in AI technology to understand the driver’s state of mind while operating the vehicle.
In an industry that I am very familiar with, the home appliance category should note that the average product development cycle is a year to about a year and a half for some products. In few cases, product development can stretch to two years from the imagination to the product launch. With AI technology, it can cut the overall product development cycle.
Using AI to Optimize Product Distribution and Pricing Strategies
With the power to drastically increase efficiencies in all areas, a report by McKinsey noted that firms could gain $1.3 trillion to $2 trillion a year from using AI in supply chain and manufacturing. I would say that AI is convenient for optimizing a product’s profitability, which is an area that we as product marketers are always facing.
AI technology can help marketers speed up the overall product distribution and help optimize the inventory’s speed and delivery to the different retail touchpoints. Further, AI’s role in supply chain management is profound, from extracting essential data from customers, suppliers to forecasting demand before products are needed.
Also, when it comes to optimizing product distribution, AI can help map the gaps and opportunities for distribution and pricing strategies. Take a look at retailers. They are continually trying to define which products to feature in the store stationed by foot traffic. Doing so requires a vigorous exercise from marketers to understand and formulate a more robust distribution and pricing strategy.
Using AI to Improve the Customer Experience
According to an MIT Technology Review Insights survey, in the future, companies might consider sharing data if it were to lead to an enhanced customer experience.
When you are on Amazon, ever notice how you see suggested products to purchase based on your online habits? That’s called predictive analytics, designed to help steer shoppers to consider buying new products based on past purchases and behaviors. Predictive analytics is an example of how AI can serve marketers better in looking at the data and then seeing what the habits are for consumers.
Before AI, brands and retailers ran focus groups, invited participants into a room, and asked them many questions, which took a long time to extract the results. So when you factor in AI and how the technology can help analyze and gather real-time data that speaks to a shopper’s buying habits, brands and retailers can create a better overall experience with ease.
As marketers, we can use AI to find out what the customers are saying in real-time and then create new user experiences tailored to their habits.
The future of AI and Marketers
While AI will continue to be more mainstream in its adoption by several industries, the marketing industry as a whole has the potential to create more overall efficiencies both internally and externally.
The August 2019 CMO Survey speaks to how prevalent AI is in marketing, with respondents reporting a 27% increase in the implementation of AI and machine learning in marketing toolkits compared to six months prior.
My advice for my fellow marketing colleagues and peers is to embrace AI with excitement and see how AI will provide value to your day-to-day work.
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