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During times of inflation and sluggish economies like we're experiencing today, large retailers and grocers typically narrow their product offerings and prioritize consumer bread-and-butter items over specialty products.
But unlike previous slowdowns, consumers today can turn to online marketplaces like Amazon to find niche products from third-party sellers.
Inventory famine to feast
During the latter half of 2021 leading up to the holiday shopping season, retailers were struggling with supply chain woes and shortages brought on by the COVID-19 pandemic, making it hard to guarantee stock of certain products throughout their busiest time of year.
In the first quarter of 2022, those supply chain bottlenecks began loosening, and many of the products that retailers ordered (up to nine months prior) came rushing into their warehouses. In an ironic twist, many retailers now have too much inventory on hand, including Target and Walmart, who cited excess inventory in recent reports.
In response, Target announced that it is offering customer discounts so it can "right-size” its inventory for the remainder of 2022. This signals that it still has unnecessary items in stock, possibly holiday-related goods, last year’s fashions and specialty items. The retailer has to burn through those products to help raise cash and clear warehouse space to purchase the consumer staples so greatly needed for the months ahead.
While that’s a significant problem on its own, record inflation this year has created a bigger mess. This, combined with other geopolitical and economic events, are driving the U.S. and global economies toward a slowdown as consumers are hit by drastically rising prices across the board.
As a result, Target and Walmart have each noted rapid changes in consumer behavior over the past two months. As they "right-size" their inventory, these big-box retailers will err on the side of having enough basic items in their grocery and home sections versus taking a chance on specialty products.
The opportunity for online sellers
That leaves a potentially big opportunity for online sellers to fill any gaps in consumer demand.
To its credit, Amazon has become a proven business incubator for third-party sellers and brands, so it's always a good time to test and launch niche products in that marketplace. It also helps that today’s consumers are already primed to go online if items aren’t available in their local stores.
In addition, if the economy continues to sour, it would be wise for online sellers to diversify their product offerings if they haven’t already done so – especially if the seller is heavily involved in luxury items. They need to ensure there are some consumer necessities in their product mix.
At Riverbend Consulting, we see several product categories that may be worth consideration in the near future, including:
- Sports/outdoors equipment
- Kids sports training equipment
- Affordable beauty supplies
- Private-label brands of popular items at a cheaper price
With specialty goods, it’s always a solid strategy to go after product ideas that you know. For example, in kids’ sports, many products came from parents who realized a need for their kids and created a product to meet that need.
There are also tools available that can help sellers evaluate potential products, how many competitors are in a given category, and if there is any value in entering that category. Two tools that come to mind include Helium 10 and SmartScout.
Whenever they can, sellers should also try to source from local suppliers to avoid any supply chain issues from overseas. Mexico is really hot right now, and many Mexican companies are looking for manufacturing work from the U.S.
If you’re looking for U.S.-based manufacturers, there are several good manufacturing directories that can help. Even your local chamber of commerce can identify manufacturers in your community. Don't underestimate local companies and organizations.
Online brands can diversify by entering retail stores
Another diversification strategy may seem ironic given that many retailers are narrowing their in-store selections, but if you’re an established online brand with favorable data (this is key!), you may have a good shot at getting your products on store shelves.
As retailers experience downward pressures, they're not going to take a chance on specialty goods that don’t have a proven track record. But an Amazon seller inherently has a lot of data at their fingertips, and if you have an interesting and winning product, this could be an opportunity for you.
There are companies such as Project Retail that help online sellers and brands evaluate, build a case and make connections in the brick-and-mortar realm to see if the retail store could be a reality.
Lesley Hensell is an Amazon seller and co-founder of Riverbend Consulting, where she and her team help other sellers solve critical business problems and grow. Learn more at RiverbendConsulting.com.
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Constructor's Eli Finkelshteyn shares principles for responsible use of generative AI, and an experiment.
This is an article about how to approach the use of ChatGPT for improved ecommerce experiences without breaking shopper trust in the process. You probably aren’t expecting Jurassic Park references, but I’m going to make one anyway.
There’s a line of foreshadowing early on where Jeff Goldblum’s character speaks about the complexities and ethics involved in cloning dinosaurs. He says something to the effect of, “Everyone got so excited that they could that they never even stopped to consider if they should.”
ChatGPT, and transformers in general (the technology underlying ChatGPT and a lot of the newer software that’s emerging in the search and discovery world) are incredibly exciting. One of the most exciting parts is how easy it is to build something with ChatGPT, and we’re currently seeing a glut of new software that does just that. Still, what isn’t clear is how to leverage this technology in ways that aren’t just gimmicks, but are actually helpful to people.
It’s clear to just about everyone that we’re in a hype cycle, and that’s why it’s so important for new technology being marketed as “powered by ChatGPT” or “powered by transformers” to prove its business value and usefulness to end users. Not to mix blockbuster movie references, but with great computing power comes great responsibility.
So it’s a good time to ask the multibillion-dollar question: how can technology companies use ChatGPT responsibly and in ways that actually benefit people in the months and years to come?
We’ve adopted some overarching principles internally at Constructor that will serve as our north star as we continue to innovate in this space. As we came up with them, we realized they could be useful as best practices for technology companies in general, and especially those like us who are serving large e-commerce companies. As more and more ecommerce leaders across B2B and B2C evaluate AI solutions in the middle of a hype cycle, we think it’s especially important to publish our principles publicly.
Our hope is that if we stick to these principles, then we’ll maintain our customers’ trust while innovating on new technology, and we’ll do this while doing the right thing for shoppers as well.
1. Experimentation is a prerequisite for ROI
Lots of companies can release a cool-looking new product and make claims about its efficacy, but it’s important for all of us to recognize that we’re early in our understanding of what applications of ChatGPT are genuinely useful to humans, and which are just science projects.
Why? Because the vast majority of those results are still unproven.
With ecommerce technology, for example, it’s important to consider whether a technology partner is going to actually deliver a product that has a legitimate impact on revenue or user happiness. Succeeding at that is ultimately a manifestation of extensive experimentation, including testing, failure, iteration, and re-testing — over and over again. Like most good things, data science takes time. It’s complex, and it’s nuanced.
Why is this so important for all of us in ecommerce tech to recognize? Because if we release a bunch of gimmicky technology and promise it’s the next big thing, then when we do come up with something useful, no one is going to trust us anymore.
The critical takeaway here is that any breathless proselytizing about most ChatGPT-based tech at this stage is counterproductive and simply not honest. If a vendor says they know for certain where the gold is right now, it’s just very unlikely to be true.
That’s the critical difference between a culture of experimentation versus one that’s only interested in shipping the “new hotness,” no matter the results. Before a product goes to market, the company that created it needs to be able to explain, and ideally prove, how it will bring ROI.
Is it just a novelty, or will it — in our case as an ecommerce product discovery company — actually help shoppers discover more products they want to buy in a way that’s more convenient, more natural, or more delightful than what they already have? And how do we know?
At Constructor, we’re excited to be experimenting with ChatGPT and large language models and transformers, both internally and with willing customers. We’re excited about the experiments we’re doing, and we hope the customers testing them are too, but we also want to be very clear that these are still just experiments. I’m providing a sneak peek at one experiment we’re very excited about below, but please read on before watching it:
Because here’s what we’re not doing: we’re not claiming we’ve invented the best thing ever. We’re not promising 10000% ROI. This is an experiment we’re excited about, but there is a real possibility that it doesn’t work out.Taking risks is what innovation looks like. The difference is that at the end of the day, our charter is to create real value (and ideally revenue) for our customers — and we won’t sell them a product that delivers anything less.
2. ChatGPT for ecommerce should be trained on ecommerce data and built for the needs of ecommerce
Ecommerce is full of unique problems and use cases for the ways people find products and content. For example, an add-to-cart and a purchase are both “conversions,” but they’re very much not the same type of conversion. Software that’s built for ecommerce has to understand the distinction, because it’s incredibly important to the KPIs that B2C and B2B ecommerce companies care about.
That’s the primary reason that we built Constructor’s AI core from scratch — the keyword-matching and vector search algorithms that work for general document search just aren’t the best technology to apply to ecommerce product discovery where you have rich feedback from users via their clickstream, along with zero party data like answers in a product-finding quiz. And the same principles apply when we apply ChatGPT to ecommerce.
The idea here is, let’s not try to boil the ocean. We don’t need to create Artificial General Intelligence that can answer every type of human query. We just need to create a very specific form of Artificial Intelligence that does one thing (helping shoppers discover products they’ll love, in our case) very, very well.
In order to return the most personalized, attractive results to a shopper’s query, ChatGPT needs to be augmented with AI models trained on ecommerce-specific data like clickstream behavior, average order values, margins, and product attributes. What’s really exciting here is that it’s the underlying technology itself that has the potential to completely reshape ecommerce. At Constructor, for example, we are working on using transformers to provide better product retrieval and filter out irrelevant results in search queries. It’s possible that this work may have the greatest impact on customer revenue, even more than the “conversational commerce” element of ChatGPT. But we don’t know yet — that’s why we’re experimenting.
(Image courtesy of Constructor)
Another advantage to training transformers on ecommerce data is that it also might mitigate some of the public concerns around ChatGPT’s accuracy. We only surface products for shoppers based on their own zero-party data and an ecommerce company’s own catalog. This heavily limits the types of wrong answers the system can give, and is about as accurate (and effective) as you can get. You may not be able to ask the ChatGPT solution at your favorite retailer about the year Albert Einstein was born, but it will be much better equipped to help you find a shirt you’ll love, or that one snack you tried and enjoyed, but can’t remember the name of. That’s a sacrifice I think most companies will be willing to make.
3. ChatGPT should build — not erode — your customer relationships
We’ll be releasing the full results in the next few months, but our team at Constructor recently performed a survey of 400+ U.S. online shoppers. We found that more than half of them were at least somewhat hesitant about using ChatGPT to find products on websites.
In our current landscape of third-party cookies and data breaches, that response is understandable. And ChatGPT could trigger a similar backlash if it makes shopping uncomfortable or intimidating. New tech can be scary, and it’s a fair concern that you might not want to ask your grocery store to create a shopping list of your regular purchases if it automatically adds sensitive items like gas relief medicine without asking you first.
We don’t have all the answers yet (as a company, an industry, or even a society) for how we’re going to solve these problems. Some of it, especially in this experimental phase, will be creating more transparency for the shopper. Expedia is an example of a company approaching this the right way, in my opinion. They recently launched a ChatGPT interface, and they’re very open about it being experimental and not trying to “trick” customers into using it. It’s a small but important step in building customer trust and delivering the value that leads to long-term relationships.
(Image courtesy of Constructor)
Questions will come up as we break new ground here. They’re important to talk and think about, and that work is the shared responsibility of retailers and the partners they work with. Ecommerce companies and their technology partners coming together to consider these murky waters — and being willing to think through new solutions to put customers first — will be absolutely critical.
A balanced approach
The amount of excitement and buzz around the (virtual) water cooler here at Constructor when it comes to ChatGPT can’t be overstated. Speed to market is a noble pursuit in this agile, volatile economy, and we are experimenting every day to figure out which of our ideas with ChatGPT and transformers will bring customer value and which require rethinking.
But we also want to balance that excitement with humility. When ChatGPT and transformers are raising legitimate questions from consumers, from companies, and even from others in the AI community, moving forward carefully and intentionally is equally important.
In this retail tech arms race, it’s the companies who widely release technology that doesn’t help their customers that have the most to lose. Ultimately, AI shouldn’t exist just for AI’s sake. Artificial Intelligence needs to yield real value if the companies using it want to be valued by their customers. We hope that our customers have come to trust us for doing right by them and their shoppers, but recognize that trust is something we have to constantly earn and maintain. My hope is these principles will help us and the wider technology ecosystem do exactly that as we embark on this next exciting adventure in AI.
Eli Finkelshteyn is co-founder and CEO of Constructor, an AI-powered product search and discovery platform tailor-made for ecommerce. This piece originally appeared on Constructor's blog, and was reprinted with permission.