How To Use Artificial Intelligence in Your Price Optimization Efforts FAQs In case you missed it, the first part of this article is here. * Here are some of the most commonly asked questions I get about Repricers, Price Optimization, and Price Intelligence. “There are so many different types of Price Optimization, it’s overwhelming. What do they all mean and which one(s) should I use?” I get a variation of this question at least once a day. I get that it’s confusing. When something has been around for a long time in the eCommerce world, it can have a lot of different names/acronyms. Plus, different segments of the industry (affiliates, marketplace consultants, SEOs) often use different names for the same things. Anyway, here are the most common you should know about… Manual Repricing: Often used in companies that don’t have very many products; small businesses; categories/areas where there is not a lot of competition or volatility; and new product introductions (which sometimes need a human touch.) Places that have a lot of inventory availability issues often do things manually as well. A Manual strategy may be implemented with an old school spreadsheet, a Rube Goldberg-type system or you may even have fancy bells-and-whistles software. The key here is that you’ve chosen to implement the changes manually, with COMPLETE oversight. Automated Pricing/Repricing: Often used in companies with huge inventories or folks who are in extremely competitive markets. Sometimes this is done in batches (Batch Automated Pricing) with oversight and other times, all the pricing is done immediately. The latter typically has tighter rules. Price Matching or Meet-or-Beat Pricing: You match or beat the competitor’s price if specific conditions are met. Price Mirroring: Helps you keep maintain real-time price parity. Companies who sell a lot on Marketplaces (Amazon, Walmart, etc.) often use Price Mirroring. Promotional Pricing: Companies who have more structured pricing often use Pricing Optimization to formulate/help with their sale prices and/or discounts/offers, even if they don’t use it for their everyday list pricing. You also see this used with companies who have large Sale, Overstock and Clearance sections or businesses who use a lot of coupon/discount/affiliate codes. Velocity Repricing: Want to sell x number of products in the next 30 days? Have a seasonal product that you have a very limited window to sell? Sell collectibles or used items? If so, you’re the ideal candidate for a Velocity-Based Pricing sales pitch. The tactics of Velocity-based repricing are covered in other areas, but this is a common term if you’re selling on eBay or other Marketplaces. Dynamic Price Optimization: All the above typically have at least a modicum amount of simple Artificial Intelligence/Machine Learning applied but Dynamic Price Automation is where the magic happens. In Dynamic Price Optimization, The Machine uses everything it knows about your business. This includes things like inventory; product status (new, exclusive, highly reviewed, etc.); competition; capacity; the overall market and its current conditions; customer behavior; and many other data points to optimize your prices PER INDIVIDUAL. You build the foundation – deciding what you want to matter and in what order, the AI/ML learns it, and then adds/enhances as it sees fit. You can choose to approve or even opt out of the additional suggestions. The Machine will 100% see things that you don’t and some of them will likely turn out to be quite valuable. “What product data is most important?” Here’s the thing… One of the best things about AI-enabled Price Optimization is that you can use ALL the data. Every last drop of it. One of the worst things is that marketers’ eyes are often bigger than their stomachs and they will try to use it all right from the jump. When you’re first starting out, keep it simple. Use things like Cost, Base Price and Floor and Ceiling prices. Your Floor Price is the lowest price you’ll accept. The Ceiling price is the highest. People often ask why you’d want to set a ceiling price. They joke and say that if someone wants to pay a million dollars for their $3 item, they’ll gladly take it. I feel the same way and you need to set ceiling prices so there’s structure for the algorithms. Otherwise, they can run amok. As an aside, if you don’t want to set ceiling prices, then your oversight needs to be VERY, VERY, VERY tight. If you have set pricing (MAP/MSRP/etc.) you’re going to want to use that information too. Be sure to include any promos/discounts/coupons if you use them. I also find that the average associated shipping price of that product is useful to include. Some vendors don’t want to deal with it, but it can be valuable, especially if you’re in a high competition area or doing a lot of paid ads. After you’ve built a solid foundation, you can add things like reviews, rating, seasonality, and sentiment scores. Some people do inventory levels right from the start and others wait a bit. “Do I have to compare my prices against the competition? Can Price Optimization be useful without major competitors? For some of our lines, we don’t have any competitors. For others we have lots but we’re never going to be the lowest price. It’s not our thing.” No, you don’t need to compare your prices against the competition. Yes, Price Optimization can be extremely useful even if you don’t have any major competition. Price Optimization helps you change the price of your products based on supply and demand. AI-powered Price Optimization predicts what and when to discount. It also tells you when and how much you can increase your prices. It does this by individual so you can factor in location (aka proximity); customer behavior; availability; and so much more We have several clients who use Price Optimization tactics without comparing their prices to anyone else’s. For example, we have a client who uses pricing intelligence to reprice things solely based on their in-house stock levels. We have several clients who use it just for segmentation (catalog and channel) and lots of B2B folks who use it for enterprise pricing. “We use Vendor X. Are they any good?” These days, most Price Optimization vendors and their “revolutionary, proprietary technology” are all incredibly similar. Your mileage will vary based on the team that you’re assigned. (Not the salesperson who pitches you, the team who works with you on a day-to-day basis.) There are definitely some vendors I like much better than others but so much of your success depends on the team you work with. I’d focus on that first. With that said, with this kind of software, a lot of the onus is on you anyway. The client is responsible for overseeing and acting on the information which brings me to… “What’s the biggest mistake companies make when it comes to Price Optimization?” Price Optimization is not a set-it-and-forget-it tactic. When you’re first starting out, you need to babysit it. Not every minute – you CAN get a little sleep – but regularly. Once you get a system that you’re comfortable with, you need to keep checking it on a regular basis. Why? Because your competitors may change their pricing strategies as a reaction to what you’ve implemented. Or maybe a new seller comes into the marketplace and disrupts everything, or your traffic increases or decreases. Perhaps you alter your search/navigation in a material way or the sentiment (ex: reviews) change and you need to factor that into the equation. Whatever the reason is you need to keep a watchful eye on things. I’d also recommend developing a solid alert system. (I’ve learned the hard way that you need to actually read all the notices though and not automatically funnel them into a “someday” folder.) “What are some easy scores when it comes to Price Optimization that you don’t think marketers know about or use?” Technically, my #1 answer should be acting upon the intelligence. Far too many folks get the findings, and they don’t use them, or they use them superficially and leave 95% of the other benefits on the table. The Vermonter in me believes something-is-better-than-nothing but it still drives me bonkers. My other low-hanging-fruits? Figuring out sweet-spot pricing. (Maximum # of sales for the maximum $ you can get, without reducing satisfaction scores.) Testing prices for new products before the product is officially launched. (This can be very lucrative.) Identifying prices for different markets, channels, and locations. Optimizing inventory levels. Determining solid action plans for the times when you are the only one (or one of the few) who have available inventory in the marketplace. Incidentally, few companies do it, but there’s also a lot of value in tying the pricing into LTV (Lifetime Value) and Sentiment Scores, if those things are important to you. Have a question about Price Optimization? Have a tip you’d like to share? Tweet @amyafrica or write email@example.com.