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Behind The Scenes Of a Market and Competitive Intelligence Platform

An introduction to the challenges that your teams should brace for in the journey of developing a market intelligence platform for information aggregation and competitive market analysis. If you are planning to build a market intelligence platform, only you will have to fight this war with irrelevant information to get to the intelligent information. Your users canu2019t understand these challenges and hence wonu2019t appreciate it. They will just see the articles that are relevant. But, if you miss any information your whole market intelligence platform will be labelled as unreliable.<br>However, if getting this right is not a priority for your business and you love to jostle with technical problems, you can try to build a market intelligence platform. This journey will leave you as a different (better) person, with a deeper appreciation for machine learning, and what it can or cannot do u2014 an important understanding to have for future enterprises.<br>Learn more about market intelligence platform at www.contify.com/<br>

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Behind The Scenes Of a Market and Competitive Intelligence Platform

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  1. BEHIND THESCENES OF AMARKET INTELLIGENCE PLATFORM Isthereawaytocaptureintelligenceandmakeitavailabletotheright audience, at the time when it is needed? How can intelligence on competitors strategies best be gathered with a market intelligence platform? Herearesomeofthebestpracticesbasedonhowleadingfirmsrun their market intelligencesystem.

  2. CHALLENGESINDEVELOPINGAMARKET INTELLIGENCEPLATFORM Identifying companiesand tagging Sourcingof information Industrytagging Removing irrelevant information Company tagsand mentions Socialmedia tagging

  3. SOURCING OFINFORMATION Theplatformhastointegratewiththousandsofdifferent websites and continuously monitor those websites to detect newinformation. Somechallengesasourcingenginefacesare: MostwebsitesdonothaveRSSfeedsandAPIs available. Therearenouniversalstandardsforwebsite development. Webscraping-Thisismorelikeadarkartwhich requires specializedskills.

  4. REMOVINGIRRELEVANT INFORMATION You can remove the non-business information right at the source.Forexampleyoucanremovestorieswiththeword “kill”butbecareful,don'tremovethestorieslike“Google aims to killpasswords..” Youhavetoremoveinformationthatisrelatedtobusinessbut not relevant to our business. For example, information about your industry but from a different geography, or information aboutyourcompetitorbutforadifferentsegmentwhereyou don’tcompete.

  5. REMOVING DUPLICATE ORSIMILAR INFORMATION Group information based on standard algorithms, then ungroup based on the other signalsinthearticle,suchastheindustry,thetopic,thecompaniesetc.Theaccuracy improveswitheachstepofgroupingandungrouping. Aftersuccessfullygrouping,youwillrealizethatalessimportantarticleisatthetopof thegroup.Sonowyouneedtosomehowmakethealgorithmsunderstandwhichisthe mostimportantarticleinthegroup.

  6. IDENTIFYING COMPANIESAND PERSONS TherearecommonEnglishwordsthat are bane to the dark world of text analyticslike: There are company names which are commonnounsorpopularwords,suchas Apple, Amazon,Gap. All this makes even more difficult for a machine to accurately recognizeentities in anarticle. Lookforwordsthathavethefirstletterin uppercase.Forexample,“ICICI”.Butnot always it turns out right like for instance,”ICICI BankQ3” Therearemisspeltwordsandfancyforeign languagewordssuchasL’Oréalthataddto themisery.

  7. ISITABOUTTHECOMPANYORJUSTAMENTION? Howdoweknowwhetherthestoryisaboutthecompanyorjustmentions thecompany? Onewaytoaddressthisproblemistoassignscorestoallthecompanies inanarticle.Butit'seasiersaidthandone. It is not a good idea to start developing and maintaining a knowledge baseforeachsignal.Youwillneedmanyasyouaimforhigheraccuracy. Rather,youshouldfindpartnerswhocanfeedussuchdataforsignals. Fortunately,manycompaniesprovidedatafeeds,whichcanbeusedas signals, viaAPIs.

  8. INDUSTRYANDTOPICSOFTHEARTICLE Youneedtofine-tunetheclassificationalgorithmsto recognize the pattern of words which are commonly usedtodescribeanindustryortopic.Eveninthis,as yougodeeper,youfindincreasingcomplexity. You will be damned if you tag a story incorrectly, and damnedifyoumissthetag.Youalsoneedtopreserve the relationships between the topic and the companies.

  9. HOW ABOUT SOCIALMEDIA? Toextractafewrelevantpiecesofinformationfromthemillionsofmindlesssharesand updates is verydifficult. Thereisanincreasingnumberofsocialmediasiteswithincreasingcomplexity. Itisnoteasytoevenfindtherightsocialhandlestomonitor.Therearefakehandles, multipledifferenthandlesofpeople,andcompaniesfordifferentpurposes.

  10. CONCLUSION Ifthesechallengesaremitigatedthentheseplatformswillnotgiveyougreat platformsevenifyouhavegreattechnologyteam Example:UberwithoverUSD8billioninfunding,usesStripeforpayment processing, and Twilio for SMS messaging. You should think hard before decidingtobuildamarketintelligenceplatform! If you are someone who depends on market intelligence or you’re responsibleforrunningthemarketintelligenceprogram,dotakeContifyfor aspin.

  11. Learn more aboutmarket intelligenceplatform Takea7-dayFreeTrialofMarketIntelligence Platform TryNow Read more at: https://www.contify.com/blog/behind-the- scenes-of-a-market-and-competitive-intelligence-platform/

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