I am dealing with problem where i have to increase the sales by product recommendation.I only have customer data and product that they have purchased.No ratings,reviews or feedback is present.What approach fit best for my problem.
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I'm exploring options for recommender systems optimized for the insurance industry, which would take into account  i) product holdings  ii) user characteristics (segment, age, affluence, etc.).  I want to stress that  a) there are no product ratings available, thus collaborative filtering is not an option  b) recommended products don't have to be similar to products that have already been purchased, thus item-to-item recommendations are most probably not relevant.  Keep in mind that in insurance you rarely want to recommend similar products to those already purchased ones, as someone with the Car insurance is unlikely to want to buy another Motor product, rather Home or maybe Travel, etc.   That's why I want to develop recommendations on similarities between the users based on their purchase history and/or demographics  Ideally, I'd like to be able to implement it in R, if not possible, then in Python. Thanks for help and suggestions!
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May’s “The Loop” blog post was just posted, you can read it . A popular response last month to our post about how we receive, prioritize and implement feedback was a question around how this framework gets utilized in the practical sense. We thought that Dark Mode was a great feature to dig down into as it was so widely requested and anticipated.   We hope you enjoy this month’s post, please leave any questions or comments you have in this thread and we will respond ASAP.
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Saw this in the reopen queue tonight    The question is closed as off-topic/general-computing and the OP apologizes for having to post it here.   Sure enough, that is what the company directs customers to do:  From:       Need some help? Ask a question on Stackoverflow with the tag    nitrousio and our developers (and other developers) will reach out to help you.      newest questions tagged nitrousio - Stack Overflow      ....list....   I guess no one anticipated that not all product support questions will be valid programming questions.  Or maybe it is about turning support into a profit center by attracting other customers.  Not sure that makes sense, though.  I mean, I'd like private support tickets when I contact a service provider.   This has been addressed previously back in 2009 by Jeff Atwood in an answer to   However, there is a newer 2012 duplicate  where the answer is effectively "OK, if..."  I thought I would post this here so the community can chime in on where the limits of this kind of thing should be and enable the proper people to take care of it.
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I recently saw a question about a problem (or possible bug) with some product on Stack Overflow. At first, I wanted to suggest that the asker post his question to that product's support forum.  When searching for the URL of that forum, I noticed that the product developer closed its support forums and now advises users to post all their questions on Stack Overflow instead.  Is this within the intended use cases of Stack Overflow, or is this abuse?
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I guess this is an additional to previous requests like  and .  But I just came across  review item, and was unable to flag it as spam.  edit: Since I posted this, the item has been removed (deleted) here is a screenshot:
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I cannot submit my answer to    I am aware that my reputation is low. Also, spam posting is discouraged.  My answer includes a compilation of Android graphing libraries, with links, so fellow hackers do not have to Google each and every one of them.  I believe this answer is superior to the current answers, because it is updated to 03/2012 and covers more than 90% of all Android charting libraries.  How can I post the answer, or how can I increase my reputation without being able to post quality answers? The old school websites included just a bunch of links to other places, I am an old man!  Alternative solution would be to blog it, and just post a link to my blog, which is not optimal.
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Let's say on www.site.com, some products are discontinued from time to time.  Each product page has nicely laid out information for users like, product features, manuals, buyers guide etc., So, in essence it's HTML, images and PDF documents.  I see two ways of discontinuing the product,  [1] Remove a product page from the website and return a 404 error.  Pro: Obsolete product pages die slowly on search engines  Con: The site returns a 404 error so, users navigate to another site as they couldn't find a specific product on www.site.com  [2] Keep the product page as it is with a message like "this product is discontinued ... "  Pro: Useful product related information remains intact, which can be helpful for users. So, if the information is unique and is not easily available on other sites then, the product page could be helpful for users.  Con: If like, 50 products exist on the site and have the message "product is discontinued" then, it's not a pleasant experience for users.  Note: Obsolete products pages might not be deleted permanently. A good example to illustrate this is, 'seasonal products'.  If a product page has a good PageRank but, is not sold throughout the year, how to deal with it?   Any pointers to resolve this issue?
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There's this side project I'm working on where I need to structure a solution to the following problem.  I have two groups of people (clients). Group A intends to buy and group B intends to sell a determined product X. The product has a series of attributes x_i, and my objective is to facilitate the transaction between A and B by matching their preferences. The main idea is to point out to each member of A a corresponding in B whose product better suits his needs, and vice versa.  Some complicating aspects of the problem:   The list of attributes is not finite. The buyer might be interested in a very particular characteristic or some kind of design, which is rare among the population and I can't predict. Can't previously list all the attributes; Attributes might be continuous, binary, or non-quantifiable (ex: price, functionality, design);   Any suggestion on how to approach this problem and solve it in an automated way?  I would also appreciate some references to other similar problems if possible.    Great suggestions! Many similarities in to the way I'm thinking of approaching the problem.  The main issue on mapping the attributes is that the level of detail to which the product should be described depends on each buyers. Let’s take an example of a car. The product “car” has lots and lots of attributes that range from its performance, mechanical structure, price etc.  Suppose I just want a cheap car, or an electric car. Ok, that's easy to map because they represent main features of this product. But let’s say, for instance, that I want a car with Dual-Clutch transmission or Xenon headlights. Well there might be many cars on the data base with this attributes but I wouldn't ask the seller to fill in this level of detail to their product prior to the information that there is someone looking them. Such a procedure would require every seller fill a complex, very detailed, form just try to sell his car on the platform. Just wouldn't work.  But still, my challenge is to try to be as detailed as necessary in the search to make a good match. So the way I'm thinking is mapping main aspects of the product, those that are probably relevant to everyone, to narrow down de group of potential sellers.  Next step would be a “refined search”. In order to avoid creating a too detailed form I could ask buyers and sellers to write a free text of their specification. And then use some word matching algorithm to find possible matches. Although I understand that this is not a proper solution to the problem because the seller cannot “guess” what the buyer needs. But might get me close.    The weighting criteria suggested is great. It allows me to quantify the level to which the seller matches the buyer’s needs. The scaling part might be a problem though, because the importance of each attribute varies from client to client. I'm thinking of using some kind of pattern recognition or just asking de buyer to input the level of importance of each attribute.
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The official documentation from Salesforce is to use Salesforce Data Extensions if you want to push tracking information from Marketing Cloud to Salesforce ().  This is what we've done but I've noticed that after creating data extensions in the data extensions folder, emails sent are still being tracked and tracking is still being sent to Salesforce.   My question is can I create data extensions anywhere and tracking will always be sent to sales cloud? what do i need to look out for to insure that tracking is being sent?
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Someone else has already asked a question about the exact same problem that I am having. Unfortunately, the question does not have an answer yet. Follow-on questions to the original poster have gone unanswered. How do I get an answer to that question?  I can't upvote the question unless I have 15 reputation.  I don't have an answer to the question (yet), although I do have some more information about my particular instance of that problem that may lead to an answer. I don't see how to just comment on the question.  What choice do I have other than to start a new post with the same question (and be responsive when anyone replies)?
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I've been lurking Stack Overflow whenever I had a problem for at least the last 2+ years. More times than not, I find my solution (or cobble one together) before I get frustrated enough to have the innernets help me with my specific custom problem.  Many times, the only commentary I would be able to add would be "thanks!" which really only wastes bits and bandwidth.  I understand implementing measures to keep the bots and SEO kids out, but sometimes it's a PITA to start participating in a community.  If you couldn't extract my question from the above rant (or title), this might be a little more clear:  Why do I require 15 reps to just up-vote something?  I feel like it's kinda silly.  Additionally, I noticed the quote off to the left:     We prefer questions that can be answered, not just discussed.   yet I have looked around here and haven't been able to find any justifiable explanation.
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I wanted to know more about . Is there any way I could get more data for this? Are there any more maps or charts to further identify where users are coming from across the world? How could I go about generating my own maps or charts?  Note: The original statistics and images provided with this question in 2009 are available in the .
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I am trying to ask a question about getting my hardware to work but I don't know what information to add to my question to get help, what do I need to do?  Related if you don't have access to a GUI:
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I am analysing some employee details to find the efficiency of the employees. Ideally I want some rankings to rank them based on these features.  My features include;   current salary projects completed customer ratings number of bugs reported customer complaints employee satisfaction profit age etc.   My target is the ranking of the employee in the job hierarchy.  I did some correlation analysis and found some features that have positive correlation (e.g., salary, projects completed, profit, customer ratings, employee satisfaction etc.).  I also found some features that are negatively correlated with ranking (e.g., customer complaints, number of bugs reported etc.)  Now, I want to use these features to make a function that reflects the employees actual rankings, so that we can use the same function to rank employees in the future.   NOTE: I am not only limited to correlations. I am happy to receive answers using other methods as well.  Is there a any good method to solve my problem.  I am happy to provide more details if needed.
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An interesting addition to the data dump would be the daily/hourly/whatever view counts for the websites. This could be used to see what happened to SO when proposal X came out, what time of day is the most active (if it was hourly), what day of the week is the most active, activity to question ratio, and many other things.   Before you say "What about Users.Views and Posts.ViewCount?", they aren't usable since they only list the total, not the breakdown of when it happened. The only statistics you could draw are monthly, which is useless.  If your worried about size, then your exaggerating what I'm asking. Daily is tiny, only 7 rows for an entire week. Hourly is a bit bigger, 168 rows per week. Considering other tables are millions of rows long, this won't affect size at all considering the growth.
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I am trying to test the impact of a sale initiative on store revenue. I have created 10 matched pairs of stores and then randomly distributed one store in each pair into a test or control group.  I then ran the sale for 21 days within the test group (keeping control constant) and measured relative lift in revenue compared to baseline.  My questions  1.) Should I be using a paired t-test based on the previous store matching  2.) Should I be measuring across each day of the test such as:          Control Test 1/1/2017    4   3 1/2/2017    3   4 1/3/2017    1   3 1/4/2017    2   3 1/5/2017    2   4 1/6/2017    1   7   Or measuring across my paired markets such as:                 Test Control Market Pair 1   10  5 Market Pair 2   8   3 Market Pair 3   5   1
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I am trying to verify that  is available in the PRO account for Marketing Cloud. Based on my research this may not be a function available. Does anybody have any idea?