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Trend Analysis: Why Retailers Are Turning to AI

Last updated: October 16, 2019

Trend Analysis  why retailers

Trend Analysis: Why Retailers Are Turning to AI

Although it’s not obvious to the casual shopper, retailers are increasingly turning to artificial intelligence to enhance their marketing and business processes. By using AI and specifically AI marketing, retailers can create better customer experiences, increase engagement, and target customers much more effectively. Between technology such as automated customer service agents, shopping advisors, and product recommendation algorithms, retailers alone are predicted to invest 5.9 billion into AI.  

How AI Helps Accomplish Retail Marketing Goals 

Retailers are increasingly using AI to optimize campaigns and provide a competitive advantage. However, artificial intelligence is not without its drawbacks. Read on to learn exactly how AI is being utilized to accomplish retail goals.

Identify, Analyze, and Engage with AI

By using artificial intelligence, retailers are able to better connect and engage with customers. AI can be utilized to identify high quality leads, ensuring your organization focuses their efforts on the most receptive and fruitful prospects. Artificial intelligence accomplishes this by finding and processing customer data, then connecting a customer’s identity and purchasing motivations to your product. This is very appealing to marketers, with 59 percent of business-to-business marketers desiring AI just for its ability to identify qualified prospects. 

The analytical power of AI can do more than find and qualify the highest quality leads. Artificial intelligence can also be used to analyze the success of campaigns and identify macro market trends. For example, AI may be utilized for brand tracking. It can determine how positively or negatively customers are discussing a certain brand or product. This task can be challenging for humans, since it involves sifting through all mentions of your brand, including reviews and social media mentions. However, artificial intelligence can quickly sift through this information by searching for certain emotional markers and concluding whether customers are sharing positive or negative experiences.

Artificial intelligence can also be used to engage meaningfully with customers and prospects. For example, men’s retailer DXL recently used an AI solution named InHabit to better communicate with their customers. InHabit creates polls, quizzes, or games related to the content that customers are currently reading with the goal of creating customer connections. This was a huge success for DXL – their engagement rate increased by 6.5 percent, and 90 percent of those engagements were from users within DXL’s target audience. This is just one way that artificial intelligence has been proven to boost consumer interest and solidify a content’s messaging.

Personalize with AI

Currently, 71 percent of business-to-business marketers are planning to use artificial intelligence to assist with personalization efforts. This is because AI can process massive amounts of customer data with great agility, and then use this data to connect with customers in novel ways. With this knowledge, retailers can better anticipate a customer’s future demands, and consequently advertise to them at the right time and place. 

One example of this is Amazon’s product recommendation engine, which evaluates a customer’s browsing and purchasing history to determine exactly which products they could want next. This pursuit has been extremely beneficial for Amazon, with the recommendation engine driving 35 percent of their revenue.

amazon product recommendations utilizing AI

This is because AI doesn’t just offer standard personalization and segmentation – it enables extremely specific, hyper-personalized approaches. This results in a very granular and specific segmentation strategy that is not feasible with human analysis alone. Statistics show that while 62 percent of marketers are talking about implementing hyper-personalization, only 9 percent of marketers are currently utilizing it. Marketers will be able to easily close that gap by implementing an AI-based approach. In turn, organizations can better cater to their customer’s individual needs, resulting in a competitive advantage.

Improve the Customer Journey and Experience with AI

Artificial intelligence can improve a customer’s experience and facilitate the journey through the sales funnel. One way that this is accomplished is via predictive analytics, which can allow your organization to forecast the future behavior of customers in relation to product offerings. 

This is accomplished by utilizing a program that can understand product data and attributes, then connecting this information to a customer’s attributes and purchasing drivers. 

One major benefit of using AI to perform predictive analysis is that while sifting through massive amounts of data, the AI can find non-traditional demand signals that can give great insight into sources of demand. For example, a café may find that if the temperature falls below 40 degrees on a weekday, sales of hot coffee increase by 20 percent. These very granular and actionable insights can often be missed by humans since the relationships may not seem particularly conspicuous.

Finally, AI can improve the customer’s experience by providing an additional level of convenience. This added convenience can benefit both the operations of the company and the experience of the customer. For example, Tommy Hilfiger is currently developing an AI service that can identify fashion trends that are resonating with their shoppers. By determining what is becoming popular among their markets, they can produce fashionable clothing before it appears on the runway. This is a great service to their customers, who can trust Tommy Hilfiger to design their apparel with upcoming trends in mind.

The Roadblocks of AI

While AI has a very promising future, there are a few roadblocks that retail leaders must overcome before they can maximize its utility. These challenges mostly revolve around the size of AI investments, choosing the right solution, and using high quality data.

The first challenge is allocating the right amount of resources to artificial intelligence. Presently, 70 percent of executives are making investments in artificial intelligence. However, out of these executives, only 50 percent are spending more than a million dollars on AI. While not every retail organization can make a huge investment in AI, underinvesting can seriously hinder efforts to find, develop, and train the AI solution. This can lead to diminished returns and missed opportunities.

Decision makers are also challenged by finding the right solution for their needs. Executives need to ask exactly what the AI platform should offer. Should it already know how to navigate business processes, or should it need to be taught how to understand these processes? Based on the answers to these questions – look at a point solution or a platform-based solution. 

  • Point Solutions: If an organization would like a solution that can do a predefined task, then they should look into a point-based solution. Unless serious development efforts are implementing, point-based solutions are excellent for the tasks they’re designed to perform, but not much else. 
  • Platform-Based Solutions: Conversely, platform-based solutions must be developed into handling the business’s specific needs. This unfortunately can be quite expensive to implement correctly, and requires finding a programmer skilled with developing and training AI.

Finally, data hygiene is an enormous hurdle for any organization seeking to use artificial intelligence. Retailers usually have a lot of data, but this data can be stored at too high of a level to be useful to these algorithms. Before data is put into any AI program, ensure it is clean, vetted, and free of errors. If this affirmation is not made, then the data can lead the AI astray, resulting in poorly developed or inaccurate insights.

Final Thoughts

Despite challenges and roadblocks with implementing artificial intelligence, retailers are able to create a competitive advantage due to the data-driven insights that AI provides. As a result, it is recommended that retailers invest in artificial intelligence, or else risk poorly executed optimization efforts. By utilizing AI, retailers are able to improve the customer’s experience and create more engaging, personalized marketing campaigns. 

 

Written by Marketing Evolution