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Explore: Search Performance and Best Practices

Cheyenne V. avatar
Written by Cheyenne V.
Updated over a week ago

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

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

Use SITE: operator with no wildcard and without http(s)://

LINK operator

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."

  1. Replace with few keywords and NEAR

  2. If the aim is to exclude PR wire syndications and you picked sentences from the boilerplates, then suggest to check out the PR wire contentCategory exclusion

  1. Melwater NEAR "industry partner" NEAR "global brands"

  2. contentCategory:"press_releases"

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

Repeated keywords

  1. wine OR vino OR wein OR víno OR vino OR vino

  2. Disney OR "Walt Disney" OR "Walt Disney Company"

Remove duplicated keywords, especially if they have wildcards attached

  1. wine OR vino OR wein OR víno

  2. Disney


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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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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