Steve Kraus is VP of marketing at emotional intelligence vendor Cogito.
What are the main ways AI/machine learning will impact marketers and their work in the next year or two?
In general, by leveraging AI and machine learning capabilities, companies can better discover patterns within data and then deliver the appropriate actions (offers, content, price) for a given customer/prospect and situation. More specifically, those discoveries will be leveraged to help better refine content, offers, ad placement and better segment customers. In addition, AI and machine learning will help to improve design and refine websites to be most effective. For example, by performing more proactive service outreach and make retention offers to key customers.
Machine learning can also increase customer lifetime value through better, more targeted, and timely cross-upsells – for instance, “you liked this” therefore, “you might also like this.” AI will also help brands better understand the impact of marketing initiatives and other company’s activities on customer sentiment. It can help target spend on the right activities and set the right goals by forecasting lead generation and sales results. This can help brands dynamically optimize pricing (based on history and known competitors) and help marketing and sales personnel have better live interactions with customers and prospects. This helps marketing and sales employees be more in tune with their behaviors in the moment and leverage that knowledge to make more appropriate offers.
In summary, what will be the long-term impact of AI/machine learning on marketing?
- Better marketing spend on the most impactful activities
- Better alignment between sales and marketing in pursuing the leads and opportunities that will lead to revenue
- Higher customer sentiment and lifetime value
- More personalized activities that result in less waste and higher conversions
- Increase customer loyalty and revenue per customer
- Happier more successful employees that are able to set and achieve proper goals
- A broader gap between the successful companies that leverage AI and those that do not
How is AI/machine learning incorporated in the work you’re doing?
Today at Cogito we are consuming AI to help us better target customers and then to detect patterns in their activities, so we can adjust how we interact with customers and prospects to get better conversions.
We are also a provider of AI technology, our technology analyzes voices within phone conversations, it can detect hundreds of behavioral signals and then based on that information, provides live guidance to service representative to help them better interact with customers during phone calls. Our AI also generates a live measure of customer perception so companies can see how their customers are feeling about them based on every service and sales call they have.
We are working with large companies to help enhance the behavior of their employees, increase productivity and provide customers with an experience that leaves them wanting to invest more in a given company.
In your experience, is AI/machine learning already affecting what brands do, or are awareness and adoption still very limited?
AI is already impacting what companies do today. It is helping to personalize content, measure sentiment, segment customers, optimize ad placement, better forecast sales and beyond.
In Cogito’s specific case, we are helping companies today have more targeted conversations with their customers and prospects through machine learning and AI. We are helping them better understand customer emotion, analyze sentiment and using that information to guide live agents to have better phones calls with customers. Our novel data is helping companies to better identify retention to inform cross-sell and upsell activities, and provide proactive outreach appropriately.
Our sentiment analysis is helping companies rapidly test and learn about new product and service offerings or marketing treatments – giving them insight into how customers react. It is helping companies run simulations or do more advanced A/B testing so they can rapidly test, learn and adapt.
