Here are seven examples where artificial intelligence is transforming marketing:
1. Content curation
Predictive analytics allows Netflix to optimize its recommendations. This kind of clustering algorithm is continually improving suggestions, allowing users to make the most of their subscription.
Uniting information from diverse datasets is a common use of AI.
Under Armour is one of the many companies to have worked with IBM’s Watson. The sports apparel company combines user data from its Record app with third-party data and research on fitness, nutrition etc.
The result is the ability for the brand to offer up relevant (personalized) training and lifecycle advice based on aggregated wisdom.
In 2015, Google admitted it was using RankBrain, an AI system, to interpret a ‘very large fraction’ of search queries. RankBrain utilizes natural language processing (NLP) to help find relevance in content and queries, as well as better interpretation of voice search and user context (e.g. Google Now).
3. Predictive customer service
Knowing how a customer might get in touch and for what reason is obviously valuable information.
Not only does it allow for planning of resource (do we have enough people on the phones?) but also allows personalization of communications.
Another project being tested at USAA uses this technique. It involves an AI technology built by Saffron, now a division of Intel.
Analyzing thousands of factors allows the matching of broad patterns of customer behavior to those of individual members.
4. Ad targeting
As Andrew Ng, Chief Scientist at Baidu Research, tells Wired, “Deep learning [is] able to handle more signal for better detection of trends in user behavior. Serving ads is basically running a recommendation engine, which deep learning does well.”
Optimizing bids for advertisers, algorithms will achieve the best cost per acquisition (CPA) from the available inventory.
When it comes to targeting of programmatic ads, machine learning helps to increase the likelihood a user will click. This might be optimizing what product mix to display when retargeting, or what ad copy to use for what demographics.
5. Customer segmentation
Plugging first- and third-party data into a clustering algorithm, then using the results in a CRM or customer experience system is a burgeoning use of machine learning.
Companies such as AgilOne are allowing marketers to optimize email and website communications, continually learning from user behavior.
6. Sales forecasting
Conversion management again, but this time using inbound communication.
Much like predictive customer service, inbound emails can be analyzed and appropriate action taken based on past behaviors and conversions.
Should a response be sent, a meeting invite, an alert created, or the lead disqualified altogether? Machine learning can help with this filtering process.
7. Image recognition
Google Photos allows you to search your photos for ‘cats’. Facebook recognizes faces, as does Snapchat Face Swap.
Perhaps the most exciting implementation of image recognition is DuLight from Baidu…Designed for the visually impaired, this early prototype recognizes what is in front of the wearer and then describes it back to them.