- AI will have profound impacts on retail in 2024, as 55% of executives say they plan to use it to assist with marketing and 39% will use it to enhance customer experiences.
- Executives who are concerned most about AI cost, technology integration, and results will find their most frequently asked questions answered below.
- Learn more about building vs. buying AI, how to get the most out of your investments, and how they will augment your teams’ workflows to deliver stronger results.
Many c-suite retail professionals have stated their intentions to invest in AI over time. In fact:
- 55% of retail execs say they’ll invest in AI to assist with marketing.
- 39% say they’ll invest in AI to enhance customer experiences.
There are no signs that these investments will slow down, as AI drives revenue, enhances brands’ online presence, finds efficiencies, and fosters customer loyalty. Let’s look at how by answering retail executives’ questions about AI.
A Cost-Focused Question About AI
Will I need to hire new people when implementing AI?
If you’re building an AI solution in-house, it’s most likely that you’ll have to hire new people. While an in-house engineering team may be able to complete portions of your build, you’ll likely need more specialized engineers, data scientists, a QA team, and a team for ongoing maintenance.
If you purchase the right AI solution to augment your workflows, rather than building it yourself, your teams can continue their current projects with no interruption.
Technology-Focused Questions About AI
Is your data set large enough?
If you’re building your own AI solution, you need to carefully consider whether you have enough data to work with, where it comes from, and if it’s truly specific enough to address your needs (which leads us to the next question).
Is your data set specific enough?
There are many all-in-one solutions out there that retailers need to be cautious of considering. While some of these solutions may promise quick results, their outputs may not be specific enough to meet your brand’s needs, due to their use of more general data, while excluding industry-specific and first party data.
Moreover, these solutions may be inoperable with the rest of your tech stack. Ideally, retailers should work with AI solutions that seamlessly integrate with the other resources their teams already use. These types of AI products are available and should be a top priority when shopping for AI. In the long term, they offer more control and flexibility.
Results-Focused Questions About AI
How will AI impact my bottom line?
Some of the biggest brands in retail—J.Crew, Bloomingdales, and thredUP—use Lily AI to drive greater sales and conversions and enhance personalized customer experiences. Beyond initial sale points, AI fosters customer loyalty, resulting in repeat purchases.
How will AI impact internal processes?
Processes that have historically been manual will be sped up. AI tags products earlier in the buying process and more accurately plans assortments, decreasing the amount of time it takes for new products to go live on your site.
AI-assisted product attribution data has significantly more depth too, with up-to-the-moment trend language and a multitude of synonyms from Lily’s 20k+ product attribute taxonomy. Rich product descriptions are also instantly generated, saving your team time writing, enhancing description accuracy, and using the language of your customers.
How will AI impact customer experience?
Shoppers will be presented with items that truly match their interests, preferences, and personal style. As a result, on-site conversions and order sizes are increased and customer loyalty is fostered through enhanced site search, product recommendations, and product copy.
Get Answers for Your Questions About AI
Whether you’re ready to implement your own retail AI, or are curious to learn more about which solution is best for your brand, experts at Lily AI can help. Schedule a demo to learn how AI helps executives achieve the metrics they care about most.