In This Article:

    Find What You Need with Salsa Knowledgebase Search

    In This Article:

      The Salsa Knowledgebase is loaded with overviews, best practices, and detailed step-by-step instructions. This is great because it means you can usually find what you are looking for. However, it also means that you need to consider how you search to ensure that you get the best results.

      In short...

      • If you are searching a phrase, enclose it in quotes. For example, "ticketed events".
      • You can use a minus sign - to exclude a word from your search. For example, searching donations returns 166 results, but searching donations -recurring returns 142 results.
      • Always read at least the first few search results. Like other search engines, the Salsa Knowledgebase search engine is powerful, so you may get many results. However, the ones that are most relevant to the exact phrase you entered will be on the first and second pages of results.
      • In your search, type the same terms that are used in the application. For example, it is better to search for Peer to Peer Fundraising than Team Fundraising.  With Team Fundraising, you'll still get Peer-to-Peer Fundraising Events, but it will be further down the list, preceded by results that are more like the literal phrase you entered than the actual term used in the application.
      • The shorter your search phrase, the better. Avoid phrases such as How do I... and focus on the key terms in which you are interested, such as Peer-to-Peer Event. So, instead of searching for How do I create a peer-to-Peer event, you would search for just Peer-to-Peer event or even just Peer-to-Peer. This will ensure that you get fewer and more relevant results.
      • If you are searching on a term that you think would be in the Salsa Knowledgebase, please open a support ticket. There's always room for improvement, and your feedback is very important.

      The Salsa Knowledgebase uses relevance scores to prioritize search results. Ideally, you'll want to keep these in mind when you search. Relevance scores are impacted by a text analysis process that considers the following factors:

      • Exact match - Results that exactly match a word in the search string. This scores higher than a stemmed match.
      • Stemmed match - Results where a word matches after stemming. For example, the plural form of a word generally matches the singular form.
      • Term frequency - Number of matches returned in a single field. Higher term frequency increases the score.
      • Field length - Matches in shorter fields score higher than results in longer fields. For example, if you have a single word search, that matches a one-word title, that will score higher than a hit in a long article title with many words.
      • Proximity boost - The score is boosted when all the search terms are close together in the same field. For example, if all the search terms are included in an article title this puts them in close proximity and gives the result higher relevance.
      • Phrase boost - In multiple term queries, exact word order is preferred. For example, when searching for “car park”, results containing "car park" are ranked higher than results containing "park car".
      • Query length - For one and two word queries, the algorithm returns only documents that match all the search words. For longer queries, 40% of the query terms must be present in a document for it to become a search result.
      • Overall quantity and quality of relevant results.
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