Reputation Management FAQ & Glossary: Every Term Explained
Reputation management has its own vocabulary, and a lot of it gets thrown around loosely by software vendors trying to sell dashboards. Below is the terminology we actually use with clients at Salterra, defined the way we’d explain it across a table, not the way a glossy sales deck would.
We’ve grouped terms by category rather than alphabetically, because most people arrive at a glossary trying to understand a cluster of related ideas — how platforms work, how metrics are measured, where the legal lines sit — rather than looking up one isolated word.
Core Concepts
Review solicitation is the practice of proactively asking customers to leave a review, typically via email, text, or a QR code at the point of service. It’s the backbone of any healthy review program, but it has rules — most platforms prohibit incentivizing reviews or targeting only happy customers while filtering out unhappy ones before they post.
Review gating is the specific (and prohibited) practice of using a pre-screening question to route unhappy customers away from public review platforms while funneling happy customers toward them. Google’s terms of service explicitly ban this on Google Business Profile, and it’s a fast way to get reviews mass-removed if discovered.
Review velocity refers to the pace at which new reviews accumulate over time — five per week versus five per year, for example. Search platforms and consumers both read velocity as a freshness signal; a profile with strong star ratings but no recent activity often reads as stale or possibly abandoned.
Sentiment analysis is the process — done manually or with software — of categorizing review text as positive, negative, or neutral, and increasingly, extracting specific themes (wait times, staff friendliness, pricing) from the language itself rather than just the star rating attached to it.
Platforms & Channels
First-party review platforms are review systems a business controls directly, typically embedded on its own website (a testimonials widget, a dedicated reviews page). Third-party aggregators — Google Business Profile, Yelp, Facebook, industry-specific sites like Healthgrades or Avvo — are platforms the business doesn’t control but must actively manage a presence on. Both matter, but they serve different purposes: first-party reviews build on-site trust and conversion; third-party reviews build external, verifiable social proof that shows up in search and maps.
Review syndication is when a review collected on one platform (often through a paid tool) gets distributed and displayed across multiple other channels — a review captured through a text campaign might get pushed to the business’s website, its Facebook page, and an industry directory simultaneously. It’s efficient, but syndicated reviews generally don’t count toward the star rating shown on platforms like Google, which only trust reviews submitted natively.
NAP consistency stands for Name, Address, Phone — the requirement that a business’s core identity information match exactly across every platform, citation, and directory it appears on. Inconsistent NAP data (a suite number here, an abbreviated street name there) confuses both search engines trying to confirm a business’s identity and the review platforms trying to attribute reviews to the correct location.
Review widgets are embeddable code snippets that pull live review content from a third-party platform onto a business’s own website, usually for social proof on service or landing pages. Not all widgets are equal — some cache reviews and go stale, others pull live and support schema markup, which matters for how that content is understood by search crawlers.
Metrics Terms
Share of voice, borrowed from PR, refers to a business’s proportion of total review volume and mention volume relative to its direct competitors within the same market and category. It’s a comparative metric — five hundred reviews sounds like a lot until a competitor down the street has two thousand.
Response rate is the percentage of reviews — usually weighted toward negative ones — that receive an owner or manager response. Response time measures how quickly that response happens after the review posts. Both are visible to anyone reading the profile and are increasingly treated as trust signals by consumers deciding between similar options.
Star rating decay describes the mathematical reality that a single new negative review pulls down an aggregate star average more sharply on a profile with few total reviews than on one with hundreds. This is why volume matters as much as sentiment — it builds a buffer against the inevitable bad review every business eventually gets.
Reputation SEO Terms
Reputation SEO refers to the practice of optimizing owned, earned, and third-party content so that when someone searches a business or brand name, the visible results skew positive, accurate, and controlled by the business rather than dominated by outdated, negative, or unrelated content.
Entity, in the search-engine sense, is how Google and other engines internally represent a business as a distinct, defined “thing” with attributes — an address, a category, a set of associated reviews and citations — rather than just a string of text. A strong, consistent entity profile is part of what makes review and reputation signals trustworthy to a search engine in the first place.
Structured data (or schema markup) is code added to a webpage that explicitly tells search engines what type of content is on the page — a review, a rating, a local business listing. Review-related schema, when implemented correctly, is part of how star ratings sometimes appear directly in search results.
Legal & Policy Terms
Defamation, in the review context, means a published statement that is both false and damaging to reputation — not simply a negative opinion. A one-star review that says “the food was cold and the wait was too long” is a legitimate (if painful) opinion, not defamation, even if it’s unfair or exaggerated. A review that fabricates a specific false claim — “this contractor is currently under criminal investigation for fraud,” when that’s untrue — crosses into defamation territory. Businesses regularly confuse the two, and it leads to wasted legal fees chasing reviews that will never be removed through legal action.
Platform policy violations are the specific, narrower grounds on which review platforms like Google will actually remove content — content that includes hate speech, is off-topic, was clearly left by a non-customer, contains conflicts of interest, or violates the platform’s own solicitation rules. This is a much lower bar to clear than proving legal defamation, and it’s almost always the faster path to getting a genuinely fraudulent review taken down.
FTC endorsement guidelines govern disclosure requirements around solicited, incentivized, or compensated reviews in the United States — businesses offering discounts or perks in exchange for reviews are required to ensure that relationship is disclosed, and outright review fabrication or buying reviews can trigger regulatory penalties, not just platform removal.
AI-Search-Era Terms
AI Overviews and answer engines refer to the summarized, conversational answers now generated by search engines and standalone AI tools (like ChatGPT or Perplexity) in response to queries — including reputation-relevant ones like “is [business] good” or “best [category] in [city].” These systems draw on aggregated review sentiment and third-party mentions, often without a click-through, which means the underlying sentiment across the web matters even when no human visits the review page directly.
Entity reputation in this context extends the SEO definition above into how an AI system characterizes a business when synthesizing an answer — pulling associations, sentiment, and specific complaint or praise themes from across the web rather than any single review source. A business can no longer manage reputation by focusing on one platform; the AI layer reads broadly and synthesizes.
Sentiment consistency is the degree to which a business’s reputation reads the same across every platform and source an AI system might draw from. Wildly divergent sentiment — glowing on Google, scathing on the Better Business Bureau — creates confusion for both human readers and AI summarization, and is worth auditing for that reason alone.
Frequently Asked Questions
Is reputation management the same thing as review management?
Review management is a subset of reputation management. Review management typically refers specifically to soliciting, monitoring, and responding to reviews on platforms like Google and Yelp. Reputation management is broader — it includes reviews, but also search result composition, press and media mentions, social sentiment, and how a business's entity is represented across the web as a whole.
What's the difference between a review aggregator and a review platform?
In practice the terms are often used interchangeably, but technically an aggregator (like a comparison or ratings site) pulls together review data that may originate elsewhere, while a platform (like Google Business Profile or Yelp) is the native destination where the review was actually submitted. Understanding which is which matters when deciding where to focus solicitation efforts, since native platforms carry more weight than aggregated displays.
Do negative reviews always hurt a business?
Not inherently. A small number of negative reviews mixed into a larger positive base, especially when handled with a thoughtful public response, often reads as more credible to consumers than a suspiciously perfect five-star record. The risk isn't the existence of negative reviews — it's an unanswered pattern of them, or a total absence of the volume needed to absorb them.
Can a business pay to have negative reviews removed?
Not legitimately, and any vendor promising guaranteed removal for a fee should be treated with real skepticism. Reviews come down only when a platform determines they violate stated policy, or in rare cases through legal action proving defamation. What a business can control is the volume of legitimate new reviews and the quality of its public responses, both of which shift how the negative review reads in context.
What does "owning" a search result mean in reputation SEO?
It means a business, rather than a third party, controls the content that ranks for searches of its own name — its website, its social profiles, its verified listings — so that the first page of results reflects an accurate, current picture rather than being dominated by outdated news, unrelated namesakes, or unmanaged third-party commentary.
Why does terminology in this space feel inconsistent across tools and vendors?
Because reputation management sits at the intersection of marketing, SEO, legal, and customer service, and each discipline brought its own vocabulary into a relatively young, fast-moving field. We've defined terms here the way we use them with clients day to day at Salterra, but expect some vendors and platforms to use slightly different labels for overlapping ideas — when in doubt, ask what specific mechanism a term is describing rather than taking the label at face value.
Terry has 30+ years in software and SEO. He’s the founder of Salterra Digital Services and SEO Spring Training, host of the Roundtable SEO Mastermind, and lead instructor at SEO University — teaching the exact tactics his team uses on client work.
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