Search performance directly affects the speed and stability of key features across the Meltwater platform, including Explore, Newsletters, Monitor, Analyze, Exporting, and the API. Inefficient or overly complex Boolean searches can cause errors or dramatically slow down response times.
By following best practices for writing efficient search queries, you can ensure fast, stable access to insights and reporting tools.
This article will cover:
Optimizing Your Searches
The issues highlighted in red are especially harmful and significantly reduce search performance.
In general, the more of these problems that occur together, the greater the negative impact.
Bad for Search Performance | Bad Example | Fix | Good Example |
Huge booleans | If we have a large query including thousands of keywords, or many large NEARs, hundreds of wildcards the query will be slow / blocked. | Try to follow all the tips in this article and minimize the query as much as possible to make it smaller and easier to execute |
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Wildcards on words with 10+ characters | internatio* [10 characters] | Use MAX 9 characters in front of a wildcard | internat* [8 characters] |
Excessive use of wildcards | D*C* | Why this is bad: The search system will look up all words of ANY length that begin with a 'D' or 'C', which is no small amount of words | DC OR "D.C." |
Too many wildcards - can often be removed | shop* | Remove wildcards as much as possible and write out different keyword versions | shop OR shops OR shopped OR shopping |
Large NEARs | President NEAR/100 Trump | Keep NEARs to 10 or less. In the majority of cases where you would use a NEAR higher than 10 an "AND" would result in the same results but with a reduced load on the system | President NEAR/10 Trump |
Wildcards in combination with NEAR | shop* NEAR center* | Remove wildcards as much as possible and write out different keyword versions | (shop OR shops OR Shopped OR shopping) NEAR (center OR centers) |
Long NOT filter exclusions | NOT 2.0 / exclusions for market research reports, stock market updates and PR wires | Use ContentCategory filters | contentCategory:("press_releases" OR "market_research_reports" OR "stock_market_news") |
Unnecessary wildcards | "example.com/*" OR "ABC:*" | Due to "tokenization", text is not only split by spaces, but also on special characters. For instance, a search for "example.com" also matches "example.com/other" → no need to add a wildcard after special characters like / : ; etc. | "example.com/" OR "ABC:" |
URL operator | url:"https://www.newsweek.com/*" OR
| Use SITE: operator with no wildcard and without http(s):// | site:"www.newsweek.com/" |
LINK operator | link:"https://www.meltwater.com/*" | Use CONTAINSLINK: operator with no wildcard and without http(s):// | containslink:"www.meltwater.com/" |
Long phrases in quotation marks | "With 27,000 global customers, 50 offices across six continents, and 2,300 employees, Meltwater is the industry partner for global brands making an impact." |
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Combining Keywords with NEAR or AND that don’t need to be combined (e.g. translations into different languages) | (beach OR شاطئ OR 海滩 OR plaža OR pláž OR strand OR plage OR παραλία OR spiaggia) NEAR/10 (volleyball OR الكرة الطائرة OR 排球 OR odbojka OR volejba OR volleybal OR volley-ball OR βόλεϊ OR pallavolo) | Combine only relevant keywords, e.g. English with English, Arabic with Arabic, Chinese with Chinese etc. → results in a lot less combinations of keywords that the search needs to run through | beach NEAR/10 volleyball OR شاطئ NEAR/10 الكرة الطائرة OR
海滩 NEAR/10 排球 OR
plaža NEAR/10 odbojka OR
pláž NEAR/10 volejbal OR
strand NEAR/10 volleybal OR plage NEAR/10 volley-ball OR παραλία NEAR/10 βόλεϊ OR spiaggia NEAR/10 pallavolo
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Repeated keywords |
| Remove duplicated keywords, especially if they have wildcards attached |
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Using Custom Categories and Combined Searches
When using Custom Categories and Combined Searches, remember:
They add complexity to the Boolean, not reduce it.
Duplicating filters across multiple sub-searches slows performance.
Example Fix:
10 business unit (BU) searches use the same 3 exclusions.
These are all combined into one search → 30 total filters processed.
Solution: Apply the exclusions only once on the final combined search (unless they are used independently elsewhere, like in a Newsletter or Dashboard).
Tips & Tricks
When constructing searches in Meltwater, it's important to understand how certain Boolean structures and operators can impact system performance. Below are key points that explain why some search techniques slow things down and what to do instead.
Wildcards
Wildcards
What’s a wildcard? A wildcard is the asterisk symbol * used to match multiple versions of a word. For example, shop* would return: shop, shops, shopping, shopped, etc.
What’s the issue? Using too many wildcards—or putting them after long root words (10+ characters)—makes searches slower. That’s because the system has to check an enormous number of word variations.
Do this instead: Use shorter root words (max 9 characters) and write out specific keyword variations where possible.
NEAR Operator Must Be Used Carefully
NEAR Operator Must Be Used Carefully
What’s NEAR? It’s a way to find words that appear close together. Example: President NEAR/10 Trump finds articles where those words are within 10 words of each other.
Why is that a problem? Larger distances like NEAR/100 require more processing power and may return too many irrelevant results. Often, just using AND will give you similar results, much faster.
Do this instead: Use smaller NEAR distances (10 or less), or use AND if closeness isn’t critical.
Avoid Combining Wildcards with NEAR
Avoid Combining Wildcards with NEAR
Why? Both wildcards and NEAR are resource-heavy on their own. Combining them (e.g., shop* NEAR center*) forces the system to calculate way more combinations, which slows things down dramatically.
Fix: Remove the wildcards and write out a few likely terms. Example: (shop OR shops) NEAR (center OR centers)
Special Characters Already Split Words
Special Characters Already Split Words
What’s happening? The search engine “tokenizes” text—it splits up words not just by spaces but by punctuation marks too (e.g., /, :, ., etc.).
Why that matters: If you search for "example.com/*", you're using an unnecessary wildcard. The system already recognizes that "example.com" includes things like "example.com/page" or "example.com:8080".
Fix: Just search for "example.com/" or "ABC:" without the *.
Using Long Quoted Phrases
Using Long Quoted Phrases
Quoting long blocks of text like boilerplates or company blurbs makes the system match that exact sentence structure, which is rarely effective and can slow things down.
Fix: Use a few key terms with NEAR. Example: Meltwater NEAR "industry partner" instead of copying the entire sentence
Repeated Keywords Are Redundant
Repeated Keywords Are Redundant
Adding the same word multiple times in a query (especially with wildcards) adds unnecessary load.
Fix: Remove duplicates. Example: vino OR vino OR vino → just write vino.
💡 Tip
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