Commentary: Four ways automated AI can ‘turbocharge’ customer analytics
You spend billions on data management platforms and products to hone your marketing.
You also track copious data to gain deep insights into customers, prospective customers, and targeted look-a-like audiences. That’s just the tip of the iceberg.
There is so much more to be done via machine learning and artificial intelligence (AI), especially as they become increasingly automated and user-friendly. You can accelerate insights, make more accurate offers related to customer intent, and regain control in the middle of a data flood and tightening regulations.
Gain meaningful intelligence now
Let’s say you’ve had a fantastic Black Friday sales boost. You’re inundated with amazing data thanks to a whole slew of new customers.
There’s one problem: manual data science, as it is currently performed, takes months to churn out one AI model. Before you know it, the holiday season is long past and spring clearance season is rolling around. The opportunity to capitalize on Black Friday sales with accessories that increase attach rates has passed.
Marketers need data intelligence now. AI-based, automated data science can take a matter of days, meaning marketing teams can address a wide range of possible scenarios and do it faster than they ever thought possible. Right away, fresh customer data can be converted into revenue.
Predict your customer’s next move
You’ve analyzed your data. You’ve gotten to know your existing customers. Now, you want to figure out who to contact, when to make contact, and with what enticing offer.
The last thing you want is to present a customer with a remarketing campaign that offers the product that was just bought. AI can be used to predict the very specific needs, desires, and likelihood-to-purchase of your customers — customers who are willing to consider customized, targeted content.
AI will predict the likelihood of a customer returning to buy an accessory, related item, or returning to shop for themselves if they were originally shopping for someone else. AI can determine what is most likely to excite someone wherever they are in engaging with your brand. Because automated AI can speed the process along, you can explore what questions and solutions lead to the biggest bang for your buck.
Let’s say that someone is actively shopping your site for clothing. Typically, they may receive a 10% off coupon, just the little nudge they need to create an account and purchase. Alternatively, a less engaged customer may need more, or something altogether different to click the “buy now” button. This is when AI can make its biggest potential impact, in the decisive moment, predicting when the customer is ready to buy and what is most likely to motivate that customer.
Take back control of your budget and your customer interactions
If you only have one chance a month or quarter to convince your customers to buy from you, you need to know when to utilize your limited outreach opportunities. You need to know what to offer. You need to predict how many prospects will unsubscribe, how many will click through to your site, and how many will eventually push the “buy now” button. AI will streamline your marketing and advertising workflow, make every touch count, and capitalize on each prospective opportunity. AI-driven engagements leave less money on the table.
One major online retail customer limits the volume of email communication with their customers. Receiving fewer, yet more relevant emails is popular with customers. AI lets them respond to fresh data quickly and turn it into meaningful touches that fit the company’s strict strategy.
With the right AI platform, business analysts and subject matter experts partner with data scientists – bringing a lot of “ad buy” control back in house, closer to the experts, and closer to the customer for more effective and targeted campaigns.
Understand why: Transparent AI
Finally, there is one big caveat. Most of the benefits of AI will not be realized without model transparency. Even if your data governance is flawless, you may struggle to comply with regulations like the GDPR, state advertising, or other industry-specific laws if you can’t say why a model generates the results it does. You need to track down any bias, and eliminate it. You may also need to explain to your executive team “how and why” certain budget allocation decisions are made. Transparent AI is a table stakes requirement for corporations that use AI to engage with customers.
Rick Saletta is senior marketing executive at Ople.
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