The martech market has exploded over the past few years, and the popularity of AI and GenAI will only increase available technology options for retail brands. According to Chiefmartech, which tracks the martech market, there are currently 11,038 available solutions, an 11% increase from 2022 — a dizzying number. Retailers looking to upgrade or modernise their e-commerce stack have their “homework” and due diligence cut out for them.
Making the wrong technology choices is not only expensive, but it also wastes time and valuable IT resources, threatening retailer’s ability to be innovative and agile in a highly competitive, margin-dependent, and fast-moving industry.
Only by asking the right questions on a fine-tuned request for proposal (RFP) that outlines a project for which businesses are seeking a desired IT solution from a prospective vendor can retailers make informed business decisions. These questions can also help brands establish clear requirements, better assess what’s on the market, and find partners that are a good fit for their business and company culture.
As the martech vendor landscape expands, it’s more important than ever to closely evaluate both the technology and the potential partner, formulating RFP questions in these four key areas:
- Can the potential partner deliver true, 1:1 personalisation? — Today’s consumers have high expectations for their shopping journeys and experiences which makes 1:1 personalisation a powerful and effective strategy for brands. Achieving 1:1 personalisation is extremely challenging, and very few vendors can deliver on its promise because retailers aim to provide personalised experiences for each customer. However, they can only do so for known and frequent purchasers for which there is plenty of data to leverage. It’s crucial to inquire whether vendors possess the necessary data streaming and deep learning technology to facilitate 1:1 personalisation in real-time — technology that is essential for delivering individualised experiences by leveraging clickstream and in-session data.
- Does the vendor link GenAI investment with ROI? — Since OpenAI introduced ChatGPT in November 2022, it, and large language models (LLMs) have sparked global interest and excitement. For retailers, this excitement has brought a higher standard for seamless, conversational shopping experiences with it. Rather than thinking GenAI can solve every problem, brands should apply Gen AI where it is most conducive to ROI, focusing on the use cases that are most valuable. According to research from the Boston Consulting Group, the most wanted GenAI feature in e-commerce is the ability to answer complex questions about products. For example, empowering customers to ask questions as part of their product research, and to be able to respond to questions such as, “what is the best lens for wildlife photography?”
As it turns out, though, while Gen AI offers new opportunities, not all implementations are created equal. Hallucinations raise significant concerns. Remain wary of solutions that use LLMs for content generation, as this is often just “LLM-washing.” In addition to firm objectives and KPIs for GenAI applications, brands should ask potential vendors questions about their strategies and ability to mitigate and minimise the risk of errors and hallucinations.
- Can you purchase both search and personalisation from the same provider? — Until recently, it was common to purchase commerce search and recommendations solutions from separate vendors. It wasn’t long before brands found this strategy would lead to potential integration issues, as well as fractured customer journeys and experiences. They’re now acknowledging the connection between search and recommendations — and are realising they should have purchased both from the same technology partner. Recommendations that truly drive tangible business outcomes in ecommerce require the ability to understand products as well as shoppers. Buying search and recommendations from the same vendor means you can leverage search signals to improve the customer experience by serving more relevant content throughout their entire journey on your website.
It also makes it easier to increase the relevance of the commerce search experiences delivered. With 30% of ecommerce visitors using on-site search and converting between five to six times higher than non-site search visitors, it’s clear that search is an important touchpoint in the customer’s shopping journey. Given how important a touchpoint it is, retailers can inject powerful personalisation capabilities into search, too, showing different query suggestions and search results based on the shopper’s profile, interests, and preferences.
- How does the vendor approach testing? – When it comes to testing, retailers should follow the lead of digital giants such as Amazon, Google and Netflix. These brands are the global leaders they are today because they listen to their customers through rigorous data collection and A/B testing. But conducting systematic, rigorous A/B testing is not straightforward. Best-in-breed search and product discovery vendors effectively balance user friendliness and scientific rigour by making it easy to experiment with large enough samples and to schedule tests to ensure random testing and avoid day-of-the-week effects. That said, to ensure conclusions are trustworthy, it’s critical that search and product discovery solutions also report on the experimental results’ statistical significance. Why is this important? Because it gives brands confidence that the changes made to their site or app have a positive impact on conversion rates and other metrics. Metrics can fluctuate wildly from day to day, and statistical analysis provides a sound mathematical foundation for making business decisions and eliminating false positives.
Finally, as more and more companies begin to offer AI-based solutions, brands should remember that not all AI is created equal. Buyers should look for best-in-breed vendors with a track record of innovation as they are likely to consistently release new features and develop critical capabilities to help thrive in the ever-evolving e-commerce world. To weed out the good from the bad, the ideal RFP should include company overview questions that investigate the vendor’s product vision and planned enhancements as well.
Andrea Polonioli is a Senior.AI Product Marketer at Coveo. Prior to joining Coveo, he was at Tooso, an AI search ecommerce startup acquired by Coveo in 2021. He has a passion for innovation-driven companies and a research background in cognitive science. Andrea is a widely cited author and has published 15+ research articles in top-tier cognitive science and information science journals. In 2023. Andrea was the lead author on an AI research paper titled, “The Ethics of Online Controlled Experiments (A/B Testing). He holds an MBA from Strathclyde Business School and a PHD from the University of Edinburgh. Andrea splits his time between Italy and Sweden.
