Modern Pricing is an API based service that helps businesses optimize their pricing through dynamic, real-time recommendations specific to individual customers.
The logic behind the offering is that some customers will pay more for the same product than others. If a business wants to maximize its profits, it needs a way to identify those that perceive greater value and have a higher willingness to pay for the same product.
The Modern Pricing Score is the recommendation the API returns based on very limited data for the business to make the right pricing decision on the fly.
Dynamic pricing made easy. Modern Pricing is an API that provides intelligent, real-time pricing recommendations.
Initial Thoughts & Impressions
We all know pricing is both challenging and rewarding when done well. Few businesses, can say they have set optimal pricing. There is frequent concerns about leaving money on the table with low prices or scaring away potential customers with prices that are too high. Any product that can help this truism deserves a closer look.
At a glance this product seems to work very similar to some forms of online fraud detection software. It is leveraging some basic site visitor information collected through the web site or app, then enriching that with third party and (potentially) proprietary data.
Example: Based on IP alone it can look up location and local demographics like income, age, crime rate, etc.
Then, based on this raw plus enriched data an analysis is run to produce a qualitative “Score” (see API doc image below). In their demo they do call this a Classification, which might be more accurate since “Score” implies something numerical to most.
My hunch is they are using machine learning to perform classification of site visitors to accomplish this feat.
It appears that, like fraud detection systems, the Modern Pricing Score is to be treated as a recommendation. From there, it is up to business logic to determine how to handle the classification returned. Perhaps there is a straight mapping of 4 price tiers, but there could be additional info not available to the API that the business uses to make the ultimate decision on which price to present.
From a technical standpoint, this seems like a really nice service to offer. It is both technically straightforward and can reduce the complexity immensely for any business attempting to implement such logic on their own.
Before going too far with any vendor that might help in an area as sensitive as pricing, I want to assess the company. Are they trustworthy? Are they mature and competent? Some online research will yield a quick initial take.
Their website looks well designed and professional. Since this is a new company to me, I wanted to get a little background on it and how they operate. A quick check up on the company using normal resources finds no mention of it under Crunchbase.com, Craft.co, Product Hunt, or LinkedIn. A possible reason for this could be that they changed their name recently or they are brand new to market.
To determine their history, I checked the Waybackmachine (web.archive.org) and find the first actual indexing of the site happened in October 2019. The content looks roughly consistent so I do a little more digging around their site for more insight.
First, they do provide a blog with an inaugural “Hello, world!” post from March 2019. So I place their start around then but there is no clear messaging on that. They activated a Twitter account on August 2019 but have yet to use it.
Whether or not their product is working already, it seems clear that they could use some basic marketing help. Not only does it make it hard to discover they exist, but it weakens credibility for potential customers that see no apparent business activity.
They do have two case studies listed. However, the first goes to a dubious looking travel website. The second is to the well-known code training site codecademy.com. While both may be legit case studies, it requires a Contact form with message to have someone contact you in a couple of days with the case study.
Customer & Problem Focus
Getting pricing right is a challenge for every business. Based on the messaging from the company website, it appears that they have broadly stated that “businesses” are their target customer.
With such a broad target market they are effectively marketing to nobody.
Based on the initial assessment of the company, it is clear this is a new product and they are likely still seeking product/market-fit. Doing so by targeting every type of business in your messaging is going to be extremely difficult.
My recommendation for this company is to dramatically narrow the focus of their marketing on narrowly targeted customer segments.
Some starting points would be:
Consumer-oriented business. Since the information passed to the API is IP and User Agent, Modern Pricing only knows about the singular web site visitor. As such it needs to be a situation where the visitor is the buyer. This can only be B2C or similar.
End Customers from Diverse Geographies. Both case studies published relate to businesses serving end customers that represent diverse geographies – across the US and/or World. Since a big piece of the pricing score algorithm relates to geography this is a must.
Lot’s of changing products. E-commerce sites with lots of unique offerings might be good candidates since visitors are unable to readily compare prices elsewhere. Any site that has just 1-5 products and publishes an often quoted/compared pricing page is dead in the water.
While the above criteria significantly focus the target, they need to go further. This may require a bit of marketing discovery work to see what resonates. If they don’t have a better starting place, I would investigate either the online education or travel markets they have case studies on.
Focusing means narrowing the messaging in all marketing channels AND focusing all outbound sales/customer development efforts. Only when they focus will they possibly find product/market-fit.
Side Note: Modern Pricing does claim to “serve as the pricing backbone for dozens of companies” with over 1 million price requests per day on their website, so perhaps they have more traction than their marketing leads one to imagine.
Based on their marketing to all businesses, effectively, they would potentially claim to have a massive market. I actually think that the particulars of their solution that recommends pricing adjustments dynamically to each customer really narrow that market opportunity.
We know dynamic pricing is a big deal in industries where there is product scarcity and variable demand today. There are many common examples:
Airlines dynamically adjust seat prices based on time before the flight, time of year, and demand.
Rideshare companies increase pricing during peak periods due to insufficient supply, with the hope of increasing that supply.
Concert tickets will increase as the event comes closer and availability is reduced.
Utilities charge more during the day than overnight based on demand variability.
These forms of dynamic pricing are not always well-received by consumers but is becoming more accepted in the market (see Price Intelligently – How Does Dynamic Pricing Work? Examples, Strategies, and Models). I believe the scale of market opportunity and acceptance is a massive unknown. As such, I would guess that they are doing a lot of work on validating market value proposition but it is not visible on anything publicly available.
The solution, as presently designed, is quite clear in its function and has a lot of precedent in other product categories. I think there is little technical risk in their offering. In fact, when adopted, it is possible to foresee them continuously enhancing the value of their API over time in a number of ways.
One of the potential challenges to getting really good scores, will be that they need feedback from the products they price. Do customers ultimately buy? Do they have repeat buys? How do different price points compare in performance under different predictive attributes? I see no reference to collecting this learning data on their website or API documentation.
Novel But Risky Application
What is novel here is the price discrimination that is occurring based solely on natural and derived attributes of the site visitor themself – not about virtues of the product features, availability, time, or changing market dynamics.
Surely, Modern Pricing has done their legal homework on Robinson-Patman Act (US), but just because you believe your service does not violate the law does not mean it will be accepted by consumers. This is a PR risk that their business customers may find not worth the potential gains.
Another risk, as their demo highlights, it is quite easy to game the pricing algorithm by manipulating your browser IP and User Agent. If you live in NYC, simply redirect through a VPN to make it appear you are located in Mexico City to save a few dollars on your online service.
Similarly, if I travel and access businesses relying on this service, what happens to my pricing? What happens if I repeatedly visit a site but from different browsers with varied settings? Certainly, I would expect to see the exact same pricing. These are issues, again, I am sure that Modern Pricing is spending a lot of effort to mitigate.
All-in-all, while the core solution is straightforward technically there are a number of risks that could upset end customer experience. Any dissatisfaction with end customers is bound to come back to Modern Pricing directly.
I got nothing. Basically, if you want to create this type of dynamic pricing as a business, it looks like it is either DIY or leverage Modern Pricing.
With a DIY approach, it will certainly be more costly to build out, but businesses can also integrate in richer consumer history and other predictive variables. Alternatively, like we see in similar online fraud prevention APIs, it is possible to use the Modern Pricing Score in conjunction with a pricing strategy that includes additional decisioning logic and factors.
Bottom line, if there is a market for this solution, Modern Pricing is in a great position to lead it by being early. However, due to no apparent moats, this may be a hard position to defend.
Pricing the Pricing API
First question I had was, is Modern Pricing using its own API to set it prices? As far as I can tell, the answer is no (but I can’t be absolutely sure).
What I can tell is that they have opted for a Freemium model that allows you to dynamically request 100 prices per month. Based on their target markets, this seems like a low quantity to me. Beyond that they discriminate based on price score requests tiers with very low marginal cost per request (e.g. $0.001/score to $0.002/score).
If you see meaningful sales conversion lift from this product, it seems to be very reasonably priced. If you implement this pricing API, it seems incumbent on you to develop a mechanism to track your visitors and ensure that you only retrieve a score one-time per visitor both to minimize unnecessary fees and reduce the risk of them seeing different prices.
This was a very interesting product to dig into. I love learning about new approaches on pricing and any products that help are worth a look.
I believe this concept has some merit but it will be in a very narrowly defined market space. Further, it may encounter legal issues in different jurisdictions around the world. To this end, I think that Modern Pricing should be doing a much better job and narrowing the scope of businesses they are attempting to market to.
Get very focused, find some product/market-fit, then expand. I would then say they need to testimonials and case studies to validate acceptance and value. Despite some reluctance among customers to talk about using them, it will be hugely beneficial to attracting additional business.