Like it or Not, Customers Are Taking Over
You’ve probably heard that the customer journey is changing. Therefore, you’re aware that shoppers are even harder to please and more likely to tune out your messaging if they find it annoying or irrelevant.
You’ve also heard the customer journey is getting longer, and the rise of mobile is a significant factor. You’ve read, right here on Total Retail, that nearly 70 percent of the 18-36 year-old demographic has “webroomed” — i.e., browsed products online before visiting a physical storefront to make a purchase.
And you know buying habits are changing. You’ve heard that two-thirds of the crucial evaluation stage of the customer journey, which comes right before purchase, is customer-controlled: reading reviews, word-of-mouth recommendations and in-store interactions.
As discussed, you know shoppers are now tuning out commercial messaging more than ever. Consider that 11 percent of all online users have used an ad blocker, up 30 percent in the past year. And you know Chrome, the world’s most popular browser, will have a built-in ad blocker to prevent irrelevant messaging from the word “go.”
And since I haven’t told you anything you don’t already know, I’m sure you already have multiple cutting-edge solutions for these challenges in place. Just like your competitors.
But for the sake of example, I’ll cover a few.
While top-of-funnel advertising like display can be good for building awareness, every penny you spend will be wasted if it gets screened out.
Therefore, it may be worth exploring deeper-funnel, intent-driven channels, such as search marketing. These are organic and paid listings that appear on search engine results pages (SERPs) on Google, Bing or Yahoo after users perform a search like “patio furniture” or “Gucci handbag.”
Why search? Users are already in market, actively seeking what you’re selling. Four out of five users actually prefer tailored search ads for their ZIP code. Shoppers actually want to hear your message … if it’s properly targeted to them.
Machine Learning-Driven Solutions
Machine learning is a subset of artificial intelligence (AI). It involves technology learning over time by observing insights derived from huge pools of data. That might sound impressive, but what does that have to do with your retail operation today?
Let’s see. Know anyone who manages huge pools of data? Like all the color/size/material/pricing info for the thousands of products they sell? These data points contain valuable insights, but they’re hard to extract from so much data. That’s where machine learning, especially used with data science (i.e., the discipline of extracting insights from huge data pools) comes into play. Here are some specific examples:
- Chatbots and voice assistants: Online merchants use machine learning-powered tools to create conversational experiences that are more engaging than just price listings. They’re also using voice assistants like Amazon Echo to drive more business.
- User engagement: Businesses like Urban Airship and Microsoft Azure use machine learning for customer retention. Using historical data, these companies’ technology predict when customers will leave, then work backwards and address potential pain points with special offers and other programs to make sure they don’t leave.
- Natural language processing (NLP): Machine learning also improves digital advertising. Going back to search marketing, ads contain individual keywords, and while some keywords are popular, “long tail” keywords are not. Something like “Nike Air Jordans 2017 Men’s Size 11” won’t have much historical data, but it might signal strong purchase intent. A machine learning system that uses NLP accurately models advertising bids even for these rare keywords, making sure they bring in as many clicks as possible at the most efficient price.
These are just a few strategies to explore to fend off the customer coup. I know … already on your radar. But a friendly reminder never hurts.
Chaitanya Chandrasekar is CEO and a co-founder of QuanticMind, a predictive advertising management platform.
Related story: Smart Advertisers Double Clicks With This Secret Weapon
Chaitanya Chandrasekar is the CEO and Co-Founder of QuanticMind. Prior to this role, he built and managed the traffic acquisition platform and was part of the Data Science team at NexTag. His experience in the industry and knowledge of platforms led to his co-founding of QuanticMind. He strongly believes in the power of data technology, which can help decipher Big Data to unlock new ideas and opportunities. Chaitanya earned his Master of Science in Mechanical Engineering from Stanford University.