MyBuys: Recommendations as a Service
In this latest installment in our series on recommendation engines, we look at MyBuys - a company purely focused on providing recommendations services to retail websites. We've noted in previous posts in this series that each recommendations vendor has a different approach. What distinguishes MyBuys is that it takes a services approach and is not based on a single algorithm. We spoke to Paul Rosenblum, VP Products & Strategy at MyBuys, who told us that most companies in the recommendations market have a "pet algorithm". However MyBuys, according to Rosenblum, uses a variety of algorithms for different contexts and different kinds of retailers. "Fundamentally", Rosenblum told ReadWriteWeb, "we don't actually have a product [...] we have a service".
We started by asking Paul Rosenblum how MyBuys compares to some of the other recommendation companies we've profiled here on ReadWriteWeb lately. He replied that MyBuys is purely focused on retail recommendations, whereas some of the others don't have such a narrow focus. For example, he said that half of Baynote's business is in the corporate space. I pointed out that ATG is also focused on retail, but Rosenblum replied that ATG is more of a platform company - i.e. focused on e-commerce products that goes beyond just recommendations.
MyBuys' Technology
The services approach means that MyBuys deploys a variety of algorithms and doesn't favor one approach - unlike, for example, ATG, which uses a method it calls "Statistical Relational Learning" (SRL). This is really the crux of the difference between MyBuys and the other companies we've profiled so far. The likes of richrelevance, ATG and Baynote all have a defining technology (usually patented) which for each is the foundation of its recommendations approach.
MyBuys has no specific algorithmic approach. Rather it appears to license technologies from companies such as Blue Martini, BroadVision, MarketLive and Microsoft. However MyBuys does still have a patent on the technology which brings all these disparate algorithms together - it calls it a "patented portfolio of algorithms".
MyBuys' recommendations are a javascript include for their clients' websites - i.e. the heavy lifting is done on MyBuys' servers. Their clients can see their stats in a MyBuys portal, and also summary stats are emailed to the clients.
Understanding Consumers
MyBuys has a team of people that focuses on site performance for its retail clients. This team - which works across all of MyBuys' client base - focuses on driving performance using a variety of tools and processes. They also do experiments for clients to find out what works best. Rosenblum noted that MyBuys is almost always paid on performance.
On its website, MyBuys says that it "creates deep consumer profiles based on both explicit information we collect from you and from shoppers when they sign up for alerts and implicit information we collect as shoppers interact with your site." Rosenblum claims that MyBuys "understands consumers at a deep level", whereas he said that its competitors don't necessarily do. He told us that the Baynote approach is "strange" because they don't focus on the individual, but rather the 'wisdom of crowds' (which he said is a 'lowest common denominator' approach). Further, Rosenblum claimed that many of MyBuys' competitors don't understand the product catalog, that they suffer from the "cold start" problem - i.e. with a new product there is no place to start, unless you know about consumer retail behavior.
Side note: we're sure that MyBuys' competitors would disagree with some of the above assertions, so we welcome feedback from them in the comments below. One thing we've found in this series is that each company in this space is very willing to talk down their competitors! A sign of a very competitive market.
Examples
On to examples of MyBuys' approach. One is World Market, a retailer of furniture and other goods from around the world. It has a 'May we recommend' section on its homepage, which Rosenblum told us is based on MyBuys' algorithms and what other people have done on the site. After the user hits the homepage, MyBuys tracks that user - they know where they came from, they pay attention to what the user clicks on next, and so on. On product pages, there are a variety of different recommendations on the right of the page under the heading 'More great finds'. The categories under this heading can differ (e.g. for some products there may be no 'featured' recommendation).
Another example is Golf Galaxy, a web retailer of golf gear. This has recommendations such as "Other great ideas" and "People also bought". It also serves up recommendations in the shopping cart: "You may also like".
MyBuys doesn't just do website recommendations, it uses email a lot. If they know the email address of the customer, they will send follow-up emails (e.g. if a user abandons the shopping cart). Rosenblum told us that this works very well, however he assured us that emails are 100% opt-in. He said that for every dollar MyBuys drives through the site, another dollar comes through the email channel.
Conclusion
So how effective are MyBuys' recommendations? According to the company, when recommendations engage consumers (i.e. a user clicks on a recommendation), they're 5 times more likely to convert than when there are no recommendations. Rosenblum told us that its clients see an increase of overall site revenue between 5-20%, which is a similar figure to that which other recommendations vendors have given us. The addition of email usually results in even higher conversions, the company claims.
As to how MyBuys compares to its competitors, as we've noted in previous reviews it's very difficult to make a judgment on that. However we're interested to note that a recommendations vendor can compete well in this market without having its own unique patented algorithm. MyBuys pushes the 'services' approach much more than the other vendors. We're sure that some of MyBuys' claims about the competition would be challenged, nevertheless it appears to be a successful business in the retail recommendations market.
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Hm. Sounds like MyBuys's expertise in the recommender systems area is only an integrational one: They don't have an own recommender but use licensed ones in parallel; They have a team to set the screws for every customer. To me, this sounds more like mechanical turk than rocket science.
Dear Richard,
Thanks again for this post on an excellent topic. However with all due respect to the companies you are profiling, it still appears unclear to me how, apart from price, they differentiate their offerings.
And I can't help feeling they tend to over-promise: "its clients see an increase of overall site revenue between 5-20%" If that were the case, why can't mybuys convince a single well recognized retailer to adopt its technology?
I think in the end, recommendation providers are all selling the same thing: baking soda they have called "tooth paste". And when it comes to choosing which tooth paste brand to buy, people tend to go for the most recognized, established brand on the market ("you can't get fired for buying IBM"). I would stay away from the little guys if I were a small retailer. Online market demand is unpredictable enough as it is without having your suppliers bailing out on you.
Sorry, I was a little gross. Maybe MyBuys can give some details on how they set the screws. What implicit and explicit user data do you use? What meta data of the items? How do you apply the data you collect to the algorithms in your portfolio because not every algorithm can cope with all types of data? Do you recognize customers across client platforms?
Dear Richard,
Thanks again for this excellent post on this emerging space. However with all due respect to the companies you are profiling, it still appears unclear to me how, apart from price, they differentiate their offerings, and how, as an online retailer, I would trust these companies will still be in business come 2010. And as a Venture Capitalist, I tend to consider myself an optimist...
To illustrate my point, let's do the math. For instance, Worldmarket.com receives about 700,000 unique visitors per month (source: compete.com). Assuming a 1.0% conversion rate, an average order size of $100, and 30% average gross margins, they must be generating something in the area of $230,000 in gross revenues per month. How much of that would they be ready to give to Mybuys? Let's say 30% of the "lift" mybuys claims to generate for them (for simplicity's sake, that would be about 30% of 20% of $230,000 = $13,800 per month.)
That means that mybuys.com makes about $13,800 per month, per client. From my experience, they're going to need a lot of clients before their shareholders start seeing any money.
I'm not criticizing the other VCs that put their money in these businesses (a couple years ago I would have probably done the same), I just think that it's important to step back and ask: is this a risk I am worth taking?
In the end, I think most of these recommendation providers are going to go out of business. They're all selling the same thing: baking soda that their marketers call "tooth paste". And when it comes to choosing which tooth paste brand to buy, people tend to go for the most recognized, established brand on the market ("you can't get fired for buying IBM"). I would stay away from the little guys if I were an online retailer and stay with the guys with the deep pockets. Market demand is unpredictable enough as it is without having your supplier bailing out on you.
Dear Richard,
Thanks again for this excellent post on this emerging space. However with all due respect to the companies you are profiling, it still appears unclear to me how, apart from price, they differentiate their offerings, and how, as an online retailer, I would trust these companies will still be in business come 2010. And as a Venture Capitalist, I tend to consider myself an optimist...
To illustrate my point, let's do the math. For instance, Worldmarket.com receives about 700,000 unique visitors per month (source: compete.com). Assuming a 1.0% conversion rate, an average order size of $100, and 30% average gross margins, they must be generating something in the area of $230,000 in gross revenues per month. How much of that would they be ready to give to Mybuys? Let's say 30% of the "lift" mybuys claims to generate for them (for simplicity's sake, that would be about 30% of 20% of $230,000 = $13,800 per month.)
That means that mybuys.com makes about $13,800 per month, per client. From my experience, they're going to need a lot of clients before their shareholders start seeing any money.
I'm not criticizing the other VCs that put their money in these businesses (a couple years ago I would have probably done the same), I just think that it's important to step back and ask: is this a risk worth taking?
In the end, I think most of these recommendation providers are going to go out of business. They're all selling the same thing: baking soda that their marketers call "tooth paste". And when it comes to choosing which tooth paste brand to buy, people tend to go for the most recognized, established brand on the market ("you can't get fired for buying IBM"). I would stay away from the little guys if I were an online retailer and stay with the guys with the deep pockets. Market demand is unpredictable enough as it is without having your supplier bailing out on you.
Richard,
Thanks for a very nice write up. I'd like to offer one clarification. MyBuys does not license our recommendation technology from Microsoft or anyone else. We use a patent pending portfolio of algorithms, some proprietary, some based on public domain approaches like collaborative filtering.
Commenters (or others) who have questions about details of our approach should feel free to contact me directly at prosenblum at mybuys dot com.
Thank you, Richard, for the continued focus on a topic that is obviously extremely important to us.
Here at ATG, we would like to point out our belief that the notion of our e-commerce platform and our platform neutral automated recommendations solution need not be mutually exclusive – we can focus on, and properly execute on both sides of the business – and indeed, the technologies woven throughout both solutions inform and empower one another. Further, we have the deep resources and experience of 18 years in the commerce business to further guide us on execution and delivery.
Our commerce platform knowledge (including our catalog expertise) is something that helps us deliver more value to online retailers who implement our automated recommendations solution – whether or not they choose our ATG Commerce Suite. This Recommendations series has largely focused on various solutions’ algorithms and how they determine relevancy. While we believe ATG Recommendations has the most predictive and personalized relevancy on the market, our solution is also different because it offers retailers the ability to refine recommendations and the reach to go beyond basic cross-sells and up-sells – and this is specifically due to our deep understanding of the catalog.
While the recommendation engine can automate the process of personalized recommendations, there are points in the shopping process where the merchandiser may want to refine recommendations to comply with a merchandising strategy. For example, 'last chance' recommendations in the shopping cart should not recommend similar items at lower price points (sacrificing revenue). Similarly, a retailer may only want to show recommendations from the same brand on certain pages. We offer our customers the ability to refine recommendations before they are shown.
Secondly, because of our rich catalog understanding and scale across large catalogs, our customers are beginning to use ATG Recommendations for much more than just recommendations. They are using the recommendations engine for automated merchandising, reaching into the catalog and displaying products to users that match their known intent but also the retailer’s merchandising strategy. Examples might be a Gift Guide populated by all products marked as “Gift” in the catalog, or a dynamic “Top Sellers” page that shows all top-selling products a retailer offers but personalized to the specific user.
Thanks for the attention – we felt it important to respond to the remark relative to catalog knowledge and our more complete commerce solution.
That means that mybuys.com makes about $13,800 per month, per client. From my experience, they're going to need a lot of clients before their shareholders start seeing any money.
Dear Steven White,
With all due respect, I feel sorry for anyone who has to work or even interact with you (should be expected for a no-name, lack of operational experience VC, but still, jus sayin).
First of all, 700,000 * 0.01 * $100 * .3 = $210,000, not $230,000. The correct monthly revenue to MyBuys per your assumptions are $12,600 not $13,800. In your "experience" they're going to need a lot of clients? No shit? As opposed to 2 customers paying them $100M/yr? What, are you upset you've yet to make a useful investment yet? Well let me help you out. When you're evaluating (or posting a 5,000 word comment on a blog) an opportunity, it helps to have some sort idea of the market landscape. Then you'd know that players like Omniture have built businesses worth multi-billions selling software-as-a-service of questionable value to the same online retailers that companies like MyBuys are targeting. And the majority of Omniture's customers pay the entry level $10k per_YEAR_ price. Let alone the $151,200/yr you miscalculated for MyBuys (multiplying monthly figure by 12 since I'm sure you missed that). Omniture (Nasdaq: OMTR) had $295M in revenue in 2008 with their market cap topping $1.9B less than two years ago.
Now, I'm not saying MyBuys is going to be anywhere near that successful. Because I don't know. Another nice tip is to check out a company's business plan, pricing and sales roadmap before making asinine assumptions of success/failure. On that note, I think all startups are going to fail. OMG, I have a 90% success rate, I must be a prophet ;)
I am running a webstore http://victoriasdeco.com, I am wondering how to use this kind of service. Can anyone tell me?