Email as the Ultimate Deal Aggregator

September 6, 2011

Almost everyone has an email id that receives deals, mailers, discount coupons, and ‘mass’ emails. Wouldn’t it be useful if email could aggregate deals, recommend related products, filter out deals that do not meet requirements and even unsubscribe to less relevant deals?

 

How would this work?

This would work by integrating email with a deal aggregation engine in the backend.

  • First, a separate tab is provided for deals. This tab will contain functionality built specifically for deals. Putting deals in a separate tab will also reduce Inbox clutter.
  • Users are asked for their preferences and targeting information such as Categories of interest, Gender, Location, Favorite merchants, Price preferences (by product category) and so on. Based on this, the deal aggregation engine would find all deals that match the user’s criteria. For example, if  the user provides “Spa Services” as an area of interest, the deal aggregation engine would fetch Spa related deals from Groupon, Living Social and other daily deal services.
  • Apart from daily deals, the email aggregator would find coupons for the user’s areas of interest. For example, if I indicated “Babies/ Children” as a category of interest, it would sign me up for Babies R Us or Target’s Baby coupons. For “Books”, it would sign me up for Barnes & Noble or Amazon coupons. I could also specify individual retailers that I like to shop at, say New York & Company, and the deal finder would crawl for their coupons and push them into my Inbox.

Here is why email is the ideal deal aggregation platform:

  • Most deal notifications happen via email subscriptions. By integrating email with deal aggregation, users do not have to take the trouble to subscribe to individual deals. They would have to indicate their preferences just one time and their email based aggregator will do the rest.
  • Email can help reduce user deal fatigue. Even though email tends to get cluttered with mass mailers, deals and coupons, it is the right medium to organize deals in such a way as to get users only the deals they want.
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How Should Recommendation Engines Deal With Multi-user Accounts?

June 12, 2011

I’ve lately been thinking about how recommendation engines handle situations where a single account has multiple users with widely divergent preferences. For example, my family has a single Netflix account, but my husband and I have very different preferences. He likes “Back to the Future” and Alfred Hitchcock movies. I, on the other hand, like “Maid in Manhattan”, “Price & Prejudice” and “The Mummy”. Won’t this confuse recommendation engines?  

 

An obvious solution is to base recommendations on categories. If someone has a preference for a romantic comedy such as ‘Maid in Manhattan”, show them another in the same category such as “My Best Friend’s Wedding”. This way, there are recommendations for the different users based on their categories of interest.

However, the disadvantage of only relying on recommendations within categories is that it does not leverage the richness you can get by having recommendations across categories. For example, people who prefer crime thrillers such as “The Bone Collector” may also like action movies such as “Terminator” and comedies such as “There’s something about Mary” Providing recommendations across categories provides many more choices and will delight users.  

The problem is that basing these recommendations on data from multi-user accounts can confuse the recommendation engine. For example, based on preferences within my account, the engine could come up with “Maid In Manhattan” for someone who liked “Back to the Future”. But this would not work for a single user account owned by a woman who only liked “Maid In Manhattan”.      

How to solve this problem?

Thumbs Down/ Thumbs Up: Letting users give the thumbs down or thumbs up to recommendations or categories of recommendations could allow the engine to give richer recommendations based on multiple categories while allowing some users to filter out irrelevant categories. In the above case, the woman with the single user account can give a Thumbs Down to “Back in the Future” (and its category) and never have to see similar recommendations again.        

A better solution is:    

Obtain multi-user information and tailor preferences: It would make sense for recommendation engines to ask if there is more than one user, and obtain the preferences of each user. This way, it can tailor recommendations for individual users. This way, for my husband, based on his interest in Alfred Hitchcock movies, it can show screwball comedy recommendations such as “There’s something about Mary”, while it would not do so for me. The UI will have to be adapted accordingly to support this.

In addition, it can also provide ‘linked’ recommendations by identifying patterns where users typically interested in romantic movies tend to have partners interested in action thrillers and sometimes tend to have children interested in Disney movies. Thus,  it can make recommendations for one user based on their partner’s very different preferences.


Extending Mint.com’s Business Model: Coupons

October 9, 2010

Mint.com’s monetization model is based on making recommendations for financial products tailored to the user’s financial situation such as bank savings accounts, credit cards, insurance or brokerage accounts. And it does so in an intelligent manner that is useful to the user. (That is the best kind of selling). For example, I got a recommendation for a savings account that offered much more interest than I was currently earning. Mint also noticed that I hadn’t been saving in my 401K for a few months and so suggested a 401K rollover account. Pretty neat, I thought, even though I did not end up using these recommendations.

Another area for Mint to monetize while providing customers with useful functionality is to incorporate Discount Coupons. Since most Mint users are serious savers focused on reducing their spending, this is a natural fit. So, based on the stores I shop at (Mint already pulls this information from my credit card and bank information to calculate my spending), it can show me coupons from retailers of interest. For example, if I’ve been shopping at Target or See’s Candies, Mint can show me Target coupons and coupons for See’s or Godiva chocolates. This should of course be non-intrusive, and could be an option on the “Ways to Save” tab.


An E-commerce Model for Social Networking

November 20, 2009

Users share birthday information, engagement and wedding announcements and many more such events with their friends on social networking sites. So why not extend this and let people buy their friends gifts for weddings, birthdays, baby showers on the networks itself? Social networking sites such as Facebook could support wedding registries – people planning to get married can sign up for a Facebook wedding registry provided by merchants such as, say, Pottery Barn or Williams – Sonoma. Their friends can then buy them their wedding gifts online. Another concept could be wish-lists – I can maintain a wish list on my profile – and any friend who is so inclined can buy it for me during the holiday season or for my birthday or anniversary.

Users should be allowed to choose whether they want their friends to see their purchases or wish lists, and if so, which friends.  It certainly should be an opt-in model.

This would require that Facebook have its own shopping engine and allow sellers to set up Storefronts. These could range from the really large stores to mom-and-pop stores. A Target storefront is different from a Target ad listing. This is because the storefront will facilitate interactions on the network itself – I can buy things from Target’s FB storefront, get coupons for the next time, share my coupons with friends, apprise them of really great deals and make suggestions (“Hey these shoes will really look good on you”, “I thought you might like this book”) – with their permission – no spam, please!

For the user, the benefit is the combination of ease of purchase and social interaction. For the retailer, the benefit is obviously the sale. Additionally, the viral nature of the site will also give them more customers. They could also derive the benefit of the targeting available on social networking sites. The site itself of course would charge listing or sales fees to the retailer which would be an additional revenue model.

Note: Facebook does have a gift shop but it is pretty basic and not as yet conducive to the wedding registry kind of concept. Also, it’s better to not just have a single gift shop, but let retailers set up storefronts and let users to buy directly from them. There are 3rd party e-commerce applications that some retailers use, but this should become a standard mainstream feature.