With next-gen technologies like artificial intelligence and machine learning quickly picking up steam in our digitally savvy ecosystem, retailers are taking the plunge and investing early in these innovations. However, there are some retailers that are hesitant in adopting these emerging technologies, but why?
Recent data reveals CMOs at retail companies admit to falling behind when it comes to implementing AI and machine learning into their businesses. Most major retailers feel they are inundated with customer data and either don’t know what to do with it or how to process it. Others sensed they fell short at tailoring recommendations, customer segmentation, and personalization.
Retailers who feel they fall into this dynamic can identify easily adoptable solutions that are leading the charge among cutting-edge retailers and combat these present challenges.
There are new versions of AI and machine learning that help streamline retailer efficiencies:
OLP, or optimized line planning, is an emerging AI-based solution that integrates data from multiple sources (like historical sales data, trend data, competitive date, CRM data, and social media feeds) to create a single view of the customer type or persona. OLP enables retailers to better understand buyer behaviors of its customers, and how they influence revenue and margins. Powerhouse retailers like Amazon are leveraging this type of aggregated data to develop private label products, placing them in direct competition with other brands and specialty retailers.
Another emerging solution is chatbots, the new trend among big retailers. Known as the digital sales assistant, chatbots are transforming and improving customer experiences in digital commerce. This, as well as other types of conversational AI, has expanded over the past year, with more than 50 companies offering these tools and technologies as a means to improve the customer-buying journey. For example, online-only brand marketplaces like Etsy purchased Blackbird Technologies to apply the firm’s image-recognition and natural language processing (NLP) to its search function.
While these new forms of AI and machine learning are useful among retailers, it’s very critical for brands to invest in the right technology stack. Because many retailers haven’t made the official leap to invest in the correct technology stack, their existing offering is missing the mark when it comes to mapping out the appropriate customer journey. An ideal starting point for these retailers is taking inventory of its current data and identifying how it is integrated for reasons of giving a complete 360-degree view of the customer.
With next-gen technologies like artificial intelligence and machine learning quickly picking up steam in our digitally savvy ecosystem, retailers are taking the plunge and investing early in these innovations.