Artificial intelligence and machine learning applications are growing in complexity. The technology is still young, but more and more businesses are seeking ways to tap into its potential.
Business owners in particular have their eyes out for AI developments related to customer relationship management. Predictive customer support, for instance, could help solve user problems even before they contact the company. Improved social media validation systems could make it easier to spot false accounts. Better analyses of CRM databases could automate finding strong sales leads.
So what does the future hold? Below, 12 members of YEC (the Young Entrepreneur Council) share the applications they’re paying attention to.
1. Social media validation
“I would love an AI application that validates social media accounts. Engagement can be faked. Followers can be bought. A bot would be the best way to scour comments and likes in order to figure out how real a person’s social media presence is. Validation for social media will become increasingly more important, especially with the growth of fake news. This will be the next wave of fake influencers.” – Artem Mashkov, DevTribe
2. Image recognition across Instagram
“We’re a consumer brand and have about 20,000 Instagram followers. What we don’t currently have is a good way to scour all of the images our fans share and engage with when they post images of Modify Watches. About 25 percent of these posts tag us in a way that we can easily find. If we can find those other 75 percent, we’ll significantly increase our engagement, traffic and, hopefully, conversions.” – Aaron Schwartz, Modify Watches
3. AI-based marketing
“Marketing in 2017 is no longer in per-CPM (blocks of 1,000 impressions) terms. It’s customized one to one with the demographics, timing and intent of individuals. Marketing automation software is starting us down that path today, but current tools are still just complex development platforms for really granular marketing. AI will do the predicting and run these one-to-one conversations in the future.” – Corey Northcutt, Northcutt Consulting Group
4. Personalized website experiences
“I see us investing more in personalized content marketing. Imagine going to a website where it knows exactly what you’re interested in. Perhaps it’s something as simple as going to a recipe website where it knows you’re vegetarian, so it only shows you the vegetarian recipes. It will take a lot of A/B testing to personalize sites to the individual.” – Syed Balkhi, OptinMonster
5. Profile building
“AI’s ability to capture and catalog large amounts of detail for each website visitor or customer will only become more valuable in the future. As more data is gathered, profiles can be built that reveal valuable information with demographics for products and services. With this information, it will become easier to ascertain the wants and needs of your customer base.” – Bryce Welker, Beat the CPA
6. Lead scoring
“Sales is a major cost center for many businesses. Much of that investment is wasted because businesses can’t accurately identify opportunities that are worth pursuing. Artificial intelligence, and machine learning in particular, will be used to analyze large data sets and develop models that can be applied to CRM data in order to identify valuable leads.” – Justin Blanchard, ServerMania Inc.
7. Personalized upsells and cross-sells
“AI offers a huge opportunity to drive upsells and cross-sells to an existing customer base. As you segment audiences in your CRM using data analysis and machine learning to gain more insight into those cohorts, you can use AI to recommend products, services and even content. This will promote a more personalized shopping experience for customers and improve the overall customer experience.” – Dan Golden, BFO (Be Found Online)
8. Predictive analyses for ad performance
“Perhaps the coolest application of machine-driven advertising is the predictive analyses of an ad’s future performance. Machine learning will also grant incredible access to data trails for marketers, and optimize bidding processes for ad impressions and RTB networks to get the most bang for your buck. This will greatly improve client campaign performance and serve customers relevant ads.” – Kristopher Jones, LSEO
9. Personalized emails
“As more companies start sending emails to their customers, forward-thinking marketers are going to want to stand out through further personalization. If you only send the content that the customer is interested in, they are more likely to click and read the emails.” – Jared Atchison, WPForms
10. Predictive customer support
“With AI, you can anticipate the customers’ needs and issues rather than react to them. The interaction between the customer and your business starts long before an issue arises, so predictive analytics can help you avoid potential technical issues and make customer support unnecessary as we know it. The higher your customers’ satisfaction with your service or product, the higher your NPS.” – David Henzel, MaxCDN
11. Affective computing
“Affective computing involves the recognition, interpretation and replication of human emotions by computers and social robots to give the appearance of empathy. As an example, Tel Aviv-based Beyond Verbal is identifying feelings conveyed by human vocal intonations and creating applications allowing machines to judge (and respond appropriately to) customer mood and frame of mind in real time.” – Alexandra Levit, PeopleResults
12. Natural language processing
“It started with IBM Watson and expanded with Amazon Alexa, Siri, Google Home and many more. Natural language processing is voice, and voice is audio. Audio saves humans time and is super valuable. An interesting fact: 1 out of every 5 Google searches is done through audio or voice. Natural language processing promises to become prominent in our daily lives and CRM.” – Anthony Katz, iNexxus