Competition in retail is higher than ever. Businesses have to find new strategic ways to stay ahead of their peers. If only brands could predict their customers’ expectations! Well, they actually can, with the help of artificial intelligence (AI) tools that convert data into valuable insights.
How do predictive analytics tools actually create value for brands? And why might dismissing them cost you in the long run?
First of all, predictive analytics provide a rich source of important insights that may seem counterintuitive. Who are your high-value customers? What motivates them to buy? Are there any specific patterns in their behavior? Having the answers to these questions increases purchase probability and may boost customer loyalty.
Knowing Your Customer
Secondly, customer expectations towards retailers are growing. People wish to have seamless experiences across channels, with saved histories and preferences. This is possible with data analytics solutions, which help you to understand each customer’s profile.
Analyzing a user’s behavior — e.g., length of interaction, angles and zoom points — might be the way to predict purchase probability and even increase it by showing the most fitting offers for that specific customer.
Predictive analytics can be helpful in numerous cases:
- it helps you analyze and categorize customers to improve sales incentivization;
- it allows you to personalize services by using purchase and browsing history to identify users’ needs and interests; and
- it finds points which drive impulse buys.
Finally, with AI-based analytics, you can optimize your ads. Personalized marketing campaigns are in full swing, and for good reason. When social media shows users relevant ads based on details they've shared, the chances of gaining their attention are higher compared to the standard, nonpersonalized approach.
You can also fine-tune your ad campaigns with the help of innovative solutions such as Cappasity.AI, a 3D analytics tool. Let’s have a look at one of the studies conducted by Cappasity together with the U.S.-based luggage retailer Samsonite.
For the study, Cappasity.AI analyzed bags and briefcases of various styles and sizes. The insights collected from almost 37,000 interactions with 3D product images on Samsonite's website were unexpected and immensely useful.
For example, it showed that zippers, pockets, and the back of the bag are of most interest to online customers. Now Samsonite can focus on the details which have proven to be most relevant for customers, instead of highlighting less important features on product detail pages.
With AI-based tools, even A/B split testing might become a thing of the past. Knowing which angles and elements are the most attractive for your customer at the launch of your campaign can enable you to immediately create the most optimal ad.
Seeing a Clear Picture
Anticipating customer needs has become as important as the quality of the product itself. Companies that take advantage of analytics are more likely to have better control of their business, knowing not only what to sell now, but also what to sell in the future.
Related story: How AI-Gathered Data Helps Enhance Customer Experience
Kosta Popov, CEO and founder of Cappasity — the company providing an easy and scalable platform for creation, embedding and analysis of 3D and AR content — has 20+ years of experience and a successful track record as a software company CEO. Under Kosta’s lead, Cappasity has so far successfully raised $8,45M. Kosta is an expert in 3D technologies, SaaS solutions and mobile applications and was named one of the top innovators by Intel Software.