Using the 70/20/10 Rule and AI to Fuel Growth
Most CMOs I know have heard about the 70/20/10 rule of marketing. This time-honored rule suggests that executives invest 70 percent of their marketing budgets into mainstream activities that generate revenue growth and are core to one’s day-to-day business competency, 20 percent into a new yet unproven innovation, and 10 percent into pure experimentation. When I bring up the 70/20/10 rule in conversations with clients, I get a look of recognition, some head nodding, and agreement that the philosophy makes perfect sense for every kind of marketing endeavor ranging from product development to marketing tactics.
So why do so many CMOs ignore the rule?
At a time when innovations such as artificial intelligence and voice assistants are rapidly changing marketing, too many CMOs are mired in the mud of managing day-to-day tried-and-true marketing tactics while their competitors prepare themselves to adapt to changing consumer behavior by investing into emerging technologies and experimenting with new business models. It’s not that investing into tried-and-true tactics such as performance media is wrong — quite the contrary, the 70/20/10 rule says you should invest most of your budget into the activities that you can prove are delivering results. But at some point sticking to your knitting delivers, at best, incremental returns, or, at worst, wasted budgets (which is why Procter & Gamble intends to slash its ad spend by $2 billion). And perhaps worst of all, you’ll fall behind savvier businesses when those emerging technologies become mainstream.
Artificial intelligence is a case in point. AI has been called “the most important general-purpose technology of our era” by Erik Brynjolfsson, director of MIT’s Initiative on the Digital Economy, and Andrew McAfee, a principal research scientist at MIT. The market for AI technologies is growing at a compound annual growth rate of 57.2 percent and will reach $36 billion by 2025. Those that master AI and the corresponding elements of data and machine learning at scale will realize tremendous advantage over competitors that play it safe and invest their entire budgets into bread-and-butter marketing.
AI has many applications, one of which is conversational commerce, or offering products and services through AI-driven conversations with chatbots. A chatbot is an automated service, guided by rules and AI, which lets users engage with a brand or company without human intervention. Communication can occur through any major messaging platform (e.g., text messaging, Twitter, Facebook Messenger, Slack, etc.) Beginning in 2015, the top four messaging apps had gained more monthly users than the top four social networking apps. Here are two examples of how brands have responded:
· Spotify relies on bots to share content. Spotify rolled out a bot on Facebook Messenger to share with users songs and albums recommended by Spotify. Spotify recently expanded the bot’s functionality to make it possible for users to share playlists with each other. One of Spotify’s competitive advantages over other streaming services is the way it uses AI to create even more refined playlists based on the activities of users and their Spotify friends. With the Facebook bot, Spotify has leveraged that advantage on the world’s largest social network.
· Mall of America, the largest retail space in the United States, uses a bot to solve a common problem in large spaces with many destinations, such as malls and sports stadiums: wayfinding. The Mall of America bot is more than a passive lists of places in the mall. The bot asks you how you want to spend your time in the 5.6 million square foot mall and what types of things you’d like to do and suggests how to maximize your time. If you’re looking for specific products often sold in multiple stores, the app tells you where to look so that you can comparison shop. The Mall of America app is a nice example of how AI can improve a customer experience by providing utility. AI need not be flashy and necessarily entertaining.
These are just two examples of mainstream businesses apply AI to deliver value to customers — not five years from now, not one year from now, but today. And chatbots are but one form of AI. Many attendant AI-based technologies such as machine learning and dynamic pricing are giving businesses an edge in the way they plan for product roll outs, personalize their customer experiences, and adapt their pricing models, thus becoming more efficient and effective.
With AI taking hold, the question isn’t why businesses should make room for AI, but why not? The reasons typically are:
· AI might confuse a CMO — which is understandable as AI is really a term for many technologies that make it possible for machines to support human judgment by going beyond processing information and analyzing and learning from it.
· A CMO is under pressure to deliver results today — and this pressure is especially acute with publicly traded companies. Consequently, it’s tempting for CMOs to stay focused on the tactics that the business believes will work now. But the problem as I’ve noted is that with better data at their disposal, businesses are challenging their assumptions about what works well and does not work so well in the first place. The tried-and-true may not be so tried and true after all.
I suggest that CMOs think about AI in context of the 70/20/10 rule. Maybe you’re not ready to elevate AI to the 70-percent category or even the 20-percent category, but find room for AI. If you’re not sure how to do so, I suggest that you:
· Surround yourself with people who will be your 70/20/10 champion. One increasingly popular solution is for businesses to dedicate resources and budget to innovation centers charged with owning questions such as how to connect innovation to customer growth. Less formal approaches include simply having the right talent in your inner circle to complement your thinking.
· Look to a partner as a source of fresh thinking. The marketplace is exploding with companies developing AI-based products and solutions (full disclosure; Moonshot, the company I work for, is one of them). In addition, you might be working with a media partner or technologist inside your company that is applying AI itself. One of the reasons Amazon, Apple, Facebook, and Google have become so influential is their willingness to apply AI themselves and help business partners to the same. Learn from your own ecosystem.
· Apply methods such as lean innovation, a product development methodology for delivering new products for people with velocity, consistency, and flexibility within the constraints of the business. The point of more agile product development methodologies such as lean innovation is to help businesses figure out how to launch new ideas quickly and eliminate ideas that are not feasible. Lean innovation is the type of test-and-learn approach that is perfect for kick-starting a new product or service using both established and emerging technologies such as AI.
CMOs don’t succeed by optimizing and playing small ball. They create long-term impact by achieving breakthroughs in service and sales. AI promises to deliver that breakthrough.