Technical Story Telling: Collective Intellect

 

Collective Intellect is a Boulder, CO, US start-up that Oracle has acquired in June, 2012.  I quit Microsoft and joined Oracle to work for this team in January, 2013.  Here is a technical story that I have used while recruiting developers into the team.

Story:

Bhargavi wanted to buy a Television (TV), so she went into doing a research by searching, reading articles, browsing different sites, different comparisons such as features, technologies.  She being a money-conscious person compared prices between different e-commerce sites such as FlipKart.com, Amazon.in, SnapDeal.com, etc.  She being a thorough researcher also researched which e-commerce sites are better, which seller is better, etc.  Finally, arrived at a TV model Samsung Smart LED TV 1357, e-commerce site, seller and purchased it.  Everyone around her appreciated her decision.

Bhavani also wants to buy TV, but she is not a researcher and trusts friends and family.  She reached out to her friends on Facebook about her desire to buy a TV as “Hi Friends, I want to buy a TV.  Any recommendations?”.  Bhargavi is a friend of Bhavani, saw the post and responded with details of her recent research, and recommendation of TV Samsung Smart LED TV 1357.

Saraswathi is another friend of Bhavani, saw this conversation and she chimed-in and responded about her ordeal  with he TV she has recently purchased.  “Hi Bhavani – I recently bought Sony Smart LED TV 2468 and I strictly recommend that you *not* go for this model”.  

 

Problem(s):

Businesses around the world want to improve their sales.  To improve their sales, they need to improve products.  To improve the products, businesses need feedback on their products.  What’s good and what’s bad about their product.  Businesses also want to reduce the damage due to their “bad” side of the product (of previous version).  Learning what’s not going good about their product in non-internet age was through feedback forms, etc.  In early internet age, businesses have sent e-mails after some time of the purchase (typically a month or two) to fill an online form.   The problem with this feedback is at the instant the form was filled, which might wary due to ongoing usage of product and it’s performance.  For example, a customer may be very happy after 1 month of usage.  But, after 6-months the same customer might be completely upset about the purchase because of other issues that have cropped up.  Knowing these issues and addressing them is very important for a business to succeed.  Reaching out periodically over an e-mail may not work out as it may be regarded as overreaching and or even spamming!.  The unhappy customers are vocal and not only the business has lost him/her as a customer, but because of their vocal nature potential future customers also refrain from their products.  In the current internet age, customers share their feedback in variety of ways – blogs, discussion boards and forums, review sites, ranking sites, social sites, etc. at the very instant they are unhappy about.  If a business can address the unhappy customer at the right time, damage can be controlled by a great margin.  Imagine United Airlines had a way to get notified about this video posted by their customer whose guitar was mishandled plus staff indifference towards the issue before going viral, how powerful would that be?

The problem with online world is there is too much of data for any company to handle.  Lot of that data is not relevant to a business.  Extracting out the relevant data (signal) out of so much data (noise) is a software problem and not a business problem (unless business is also about a software). 

Adding to this, issues of a product may not be global but local, may be due to the local environment or manufacturing site, or some other.  Aggregating and drilling into this information at ease would be a huge plus for any business.  

 

Solution:

Collective Intellects collects the textual data from all the online media such as blogs, news, forums, boards, review sites, social sites, etc.   Analyze all the data (mostly noise) to extract important information (signal).  In this process, the product drops most of the data as the online is full of conversations that are not related to businesses using Natural Language Processing (NLP) domain algorithms. 

In the above story, the discussion is around Entity “TV”.  Bhavani’s post contains “Purchase” language ,  Saraswathi’s response contains a “Support” language, Bhargavi’s response contains “Promotion” language.  It is these meanings that Collective Intellect identifies and then shares the information to TV Companies if they are our customers.   Customer’s can then route this information to appropriate departments with in their company, such as “Support” language events becoming a Support ticket, “Purchase” Language becoming a “Sales” lead, “Promotion” language becoming a “Loyalty” Program.

To give you an idea of this working in real world, have you observed this in Facebook?

Laxmi: I am completely fed-up with my Vodafone connection.  While my SIM Card works well, my wife’s SIM Card does not work in the same house.

Vodafone Customer Care:  Dear Laxmi, We are really sorry for the inconvenience caused.  Can you please share more details of the problem such as which SIM Card is working and which is not,  the locality, etc. so that we can dig deep.

Laxmi: Here are the details.  Working SIM: 1234567890, Failing SIM: 9876543210, Location: Hyderabad

Vodafone Customer Care:  Based on our backend analysis, we think that SIM Card is corrupted.  We dispatched a new SIM Card to you, please try and let us know. 

Laxmi: I received the SIM Card and it works well.  Thanks for resolving the issue.

Wondered, how can Vodafone Customer Care know that Laxmi has posted about them of all the Facebook users and also a particular post that is targeting them of all the posts Laxmi made?  The magic behind that is the products like Collective Intellect.

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