keyword search vs discovery white paper

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Want to locate tools to monitor social media conversations? Easy -- a keyword search will reveal individual tools, lists of tools and even reviews of tools. But if you want to know what business users are really saying about those tools and the experience of using them, there is a better way. In this white paper, we explain why keyword search isn’t the end-all for marketing professionals when it comes to social media analysis — especially for those who view themselves as marketing technologists. We explore the shortcomings of keyword search. And we introduce an alternative: thematic discovery.

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  • 1. White PaperKeyword Search vs. Discovery1 West Street New York NY 10004 | 646-545-3900 | [email protected] | networkedinsights.com

2. White PaperNetworked InsightsKeyword Search vs. DiscoveryMany tools are available to marketers for monitoring social mediaconversations. And it isnt hard to find them. Just do a keyword search. Thematic discovery can help uncoverIdentifying these tools by using a search engine is particularly fitting,because most of those tools employ some form of keyword search as theWhat topics are being discussed incornerstone of their technology. And for many information retrieval tasks, connection with the users andkeyword search works well. competitors brandsBut search isnt always the answer for marketing professionals How the volume of the usersespecially those who view themselves as marketing technologists whoconversations compares to thatare growing ever more sophisticated in their approach to social mediaof competitorsanalysis. Sometimes, search-based approaches are by nature flawed, pro-ducing information that is misleading or inadequate. Even if the informa-What unexpected topics are beingtion is on target, assembling and analyzing it can take a painfully long time. discussed by a given group of peopleSearchs limitations are especially evident when the goal is to uncoverHow the users and competitors PRthemes emerging from peoples social media conversations without and marketing efforts changed the wayinjecting into the analysis any preconceptions of what they will be talkingpeople talk about brandsabout. In other words, when you truly want to find out what you dontknow, search may be as likely to send you down rabbit trails as it is toreveal the truth.Thematic discovery is an alternative approach to search that can providea more accurate, authentic view of the topics that people are engaged in.Along with identifying key themes within a social media data set, thematicBrandsdiscovery can help in identifying relationships between themes that maynot have an obvious connection, how the themes correlate, and wherepeople are likely to be talking about them simultaneously. Such informa-tion can help marketers develop media plans, choose celebrities to en- Musicdorse products, and tap into the diverse interests of their target markets. TVThis white paper discusses the uses and limitations of keyword search-based tools and the key characteristics of a thematic discovery tool thatcan provide insights that search cannot. MoviesGames2 3. White Paper Networked InsightsKeyword Search vs. DiscoveryWhen search works wellKeyword search is an indispensable tool for virtually anyone who uses theInternet. It is most effective when:You know exactly what youre looking for. Search does an excellent job offinding specific items of information.You have a narrow range of acceptable, predetermined results. Searchalso works well when you have in mind what the results should look likeand say.You only require a few answers to your question. Top search results can be traditional searchon target, but the farther down the list you go, the less likely the resultsare relevant to what you are looking for.Very specific matches are the desired output. Search emphasizes specificmatches of terminology because it relies on the language that you pro-gram into the search box. Search emphasizes specificContext is not important or even valuable. Search works well if all you matches of terminology becausewant to do is find something, but you dont care where it came from orwhat its about. it relies on the language that you program into the search boxWhy search stumblesWhile the characteristics of search make it work well for finding specificinformation items, it has several limitations when conducting thematicanalysis:Keyword search introducesconsiderable distorting biases to results.Performing a keyword search requires you to create a list of words andphrases, which by definition, reflect your expectations of the themes thatwill be present in a given data set. That expectation introduces a biasin the results because the search will not find results outside of thosepredefined keywords. If, for example, you try to learn from conversationsabout smartphones, you will need to develop a search query that lists allthe topics and brands that you think will be present. But there is no wayfor that query to find topics or brands that are not included in the keywordstring. In other words, you cant search for something unless you have anidea of what youre searching for.Another factor potentially influencing search results is prosecutors fal-lacy. This is the statistical phenomenon that, in a large data set, no matterwhat youre looking for, you will find it, regardless of whether it is statisti-cally important or valid.3 4. White Paper Networked InsightsKeyword Search vs. DiscoverySearch can miss relevant data sets.While keyword search can yield a lot of data, several issues can diminish itsusefulness and efficiency when applied to thematic analysis:Lack of fluency in the vocabulary being used. In keyword search, a user canmisunderstand the subtle differences in how people talk about the sameconcept. Thematic discovery provides the ability to identify similar con-cepts even if the language used to describe those topics varies.Search results may not produce enough relevant responses. Using searchto find themes may not produce a statistically valid sample. Again usingthe smartphone example, a search for street-map applications may deliver traditional searcha few highly targeted results, but it will likely not yield enough data pointsto constitute a statistically valid sample of the entire data set. Many lowerranking results from a keyword search will not even be about the intendedsubject matter at all.Lack of context to bridge result sets. Keyword search delivers an orderedlist of individual results ranked by relevance to the search query. But thereis no additional information provided to help the user understand how the Search cannot contemplateresults relate to each other. By contrast, thematic discovery not only iden- the context of how wordstifies the themes that are present in a given data set, but also describes and phrases are used inwhether those themes connect to one another, and if so how. Oftentimes,the context of the results is as valuable as the results themselves. relationship to one another; it simply can identifyMultiple word meanings make searching for themes more difficult. Say theword apple, and someone may think about a food, a company or a com- whether or not that word orputer. Differentiating these meanings with a keyword search tool requiresphrase is present.complex queries containing many exclusions. The longer the query, thelonger it takes to build and process that query, and the greater the chanceof human errors as terms are added.Search can be time consuming and costly.Understanding multiple themes requires developing multiple keywordsearch queries. Every theme within a data set will require its own tailoredsearch. The broader the analysis, the more time intensive it becomes.Highly manual processes are required to measure, compare and trendsearch results. The ranked results from a keyword search are typically not ausable format for further types of analysis. Specifically, performing the-matic discovery from those results requires considerable manual effort toconvert the data into consumable information.Traits of a good thematic discovery toolThe goal of thematic discovery is to understand the prominent topicswithin a given data set and how they relate to one another. The resultinginformation can help answer critical business questions.4 5. White Paper Networked InsightsKeyword Search vs. DiscoveryAn effective thematic discovery tool can help users:If you are trying to find out whatEliminate as many user biases as possible. A discovery tool needs to pro-duce organic results uninfluenced by the user. In any discovery initiativepeople really think about yourits imperative to avoid injecting what you know into the process.brand, markets, products andcompetitors, thematic discoveryIdentify all the themes present in a data set. You can use search toidentify themes you know about, but how do you look for something will enable you to approach thethat you didnt know was there? A discovery tool should uncover every task without biases, capture alltheme present.key conversations and gatherExplain the relative size of themes and whether they are gaining or losinginformation quickly.momentum. Comparing themes can show which are capturing the largestconversations and how the themes are trending against one another overtime.Provide the flexibility to change the granularity of the analysis. Ideally,a discovery tool should allow users to define the size of a theme that isimportant to them. Are you looking for the three or four most importantthemes, or for outliers? In some cases, outliers may be valuable to mar-keters because they help identify previously unidentified niche markets.A good tool will enable the user to look at various levels of granularity inQuestions about this report? Wantthemes. to learn how thematic discovery canimprove your marketing decisions?Separate noise from the signal. In any given discovery process there will besome data points that have no value on their own and do not relate mean-ingfully to any other part of the data set. The tool should eliminate these Let us know by visitingpoints from the data set to prevent clouding the results.www.networkedinsights.com/contactUnderstand the relationship between those themes. What is the likelihoodthat someone might be talking about any two or more themes at a time?Statistics can provide those answers and a good discovery tool will not justfind the themes but also identify the number and strength of correlationsthat exist between them.Work quickly and efficiently. The process of defining the data set forthematic analysis