Merchandising in the AI era

Feb 8th 2024ecommerce

For merchandisers, every website visit is an opportunity to promote products to potential buyers. In the era of AI, incorporating data into this process can drive significantly better results for merchandisers. AI-enabled merchandising uses data to make decisions fast, and these capabilities can complement merchandisers’ business knowledge to display the right products at the right time — customized for each visitor. With the right setup, AI can crunch real-time data to boost the probability of conversion for each interaction.

However, for AI to work, it still needs a human touch, too. As we’ve seen with AI tools like ChatGPT and Midjourney, while the result can often feel impressive, AI still lacks the empathy and aesthetic of real people which is important in creating a highly personalized shopping experience. However, AI can help resource-strapped teams fill in the gaps and augment human-driven campaigns today.

In this blog, we’ll explore how AI can help with merchandising. Keep reading to learn more, or download a free ebook on the future of merchandising for the AI era.

Merchandising evolved for digital commerce, and it’s evolving again in the era of AI

With so much economic uncertainty, every business is concerned about cost management. Merchandising has typically been focused on high-impact sales, new collections, and seasonal promotions. AI is capable of augmenting these efforts and filling in the gaps.

AI-powered site search boosts the highest converting results to the top for any query. Similarly, dynamic collections can be reordered and optimized at load time. The same data can be leveraged for driving high-converting recommendations at check out. Furthermore, AI-personalization can be applied at each step to provide the products that match a buyer’s affinities and preferences

The common denominator for any AI product is data. The more data you have — by category, product, customer, past browsing and buying behavior, etc. — the better performance you’ll see from AI.

Data is key

Many companies are investing in data warehouses to analyze ecommerce behavior. AI needs the same data. Positive “signals” and success metrics such as clicks, views add-to-cart, rating and reviews, signups, and purchases are leveraged by AI to build models for success. Other data such as returns, products, and stock, or even competitor pricing, can also be used for building AI models.

AI has a real advantage of speed. Fed with a consistent stream of fresh data, AI tools can adapt merchandising strategies that react in real-time and respond to variables such as fluctuations in buyer behavior, stock, and pricing. AI will collect a wide range of data through events and use it to automatically re-rank products with user-set rules and relevance algorithms.

However, that doesn’t mean merchandisers are sidelined. With Algolia, merchandisers have the option to also adjust and A/B test different models to supercharge results even faster. AI-driven tooling makes it easier to constantly test and adjust winning formulas thereby keeping pace with market trends and responding before competitors can.

For example, a retailer has a goal of pushing all winter coats out the door before the season ends in a month. This would require the merchandiser to forecast the sell-through rate and periodically adjust the promotion or pricing over the next few weeks. AI takes the workload of these mechanical tasks off the merchandiser. It can continuously analyze, re-forecast, and automatically adjust in real-time throughout the entire month until the last jacket is sold on the last day of the season at the highest possible price.

Less pinning, more AI automation

Merchandisers using AI-powered tools will rely less on rules to reach specific goals. Pinning will be used sparingly to override the AI only in special situations – for example for a limited time promotion of a new brand launch or sponsored product placement.

Instead of intervening at the level of individual products, merchandisers will define goals and objectives at a broader strategic level. For example, merchandisers may configure the AI to “adjust the ranking to promote the knitwear collections to clear down discounted stock, prioritize gross margin on outerwear, and give increased exposure to new dresses over the weekend.”

AI can analyze historical sales data to more accurately forecast the performance of new products before they are purchased to help determine optimal quantities and price points. AI can also better understand customer intent as they browse your site and tailor their search results – thereby improving conversions and sales. Additionally, revenue analytics data can then be used by the B&M team to accurately predict stock that drives the highest revenue.

Finally, the same AI that powers your site search engine can also be used for dynamic browsable product pages, personalization, and recommendations. By leveraging the same platform, you can build a success flywheel that optimizes results throughout the customer journey.

Get started with AI today

With an AI-powered tech stack combined with a data-driven strategy, merchandisers will be able to craft unprecedented customer journeys such as an omnichannel retailing experience in the ‘phygital realm’ – a convergence of physical and digital marketplaces where customers seamlessly shop online, in-store, a combination of both, or through other channels like phone and email.

Download a free ebook on the future of merchandising for the AI era to learn more, or sign up today to speak with one of our experts.