Research checked 2 October 2026. This is a comparison of documented products and purchasing workflows, not a hands-on accuracy benchmark.
Semrush and Ahrefs belong on the shortlist when you need to investigate search demand, compare competitors and monitor AI answers. Beacon by EVAA offers SaaS monitoring and separately scoped catalogue-grounded branded assistant implementation. A company may need a research platform and implementation work at the same time.
The useful question is what your team will receive after it finds a problem. A dashboard can show that your product is missing from an answer. Your team still needs to identify the cause, decide what it can change, make the correction and check the result. An assistant implementation adds another set of responsibilities: the data it can access, the actions it can take and the conditions under which a customer can use it.
Start with those jobs before comparing subscription prices.
Choose around the work you need to finish
| Buying situation | Sensible starting point | Evidence to request before choosing |
|---|---|---|
| Your SEO team needs category research and AI tracking alongside its existing search workflow | Examine Semrush’s combined toolkit and Ahrefs’ research/tracking options | Relevant queries, source coverage, current exports and a demonstration of the exact reports the team will use |
| Your brand already appears in many AI answers and you need to investigate the wider category | Examine broad-domain and competitor research in both platforms | Which questions, markets and dates make up the research database, and how your entity is matched |
| You have a fixed list of important buyer questions | Compare custom prompt tracking on the required surfaces | Exact questions, cadence, locations, unavailable-answer handling and recurring cost |
| AI answers contain an old price or the wrong warranty | Evaluate the monitoring tool and the team responsible for correcting source information | A claim-level record linked to the right product, market, source version and proposed correction |
| You want customers to use a branded assistant grounded in your catalogue | Evaluate a specifically scoped implementation, including Beacon where it can demonstrate the required workflow | Actual connection and invocation requirements, permissions, current product data, failure behavior and maintenance ownership |
The last two situations require more than a list of mentions. They need an accountable correction or implementation process. They also require separate acceptance tests: appearing in an unconnected search answer and completing a task inside a connected branded assistant are different observations.
These are starting points for a shortlist. They are not claims that one vendor has exclusive access to a category of work.
Semrush: inspect the report you intend to use
Semrush’s AI Visibility Toolkit includes brand and competitor research, custom prompt tracking, sentiment analysis and AI-related site checks. Its documentation also describes Semrush One as a combined SEO and AI Visibility purchase. For an existing Semrush team, that may reduce the effort needed to move between research, technical investigation and reporting. Semrush’s toolkit documentation
The main purchasing detail is that the toolkit contains several datasets. Semrush describes its research database, Brand Performance reports and custom Prompt Tracking separately. It says the research data draws on AI interaction and search datasets, while custom tracking queries selected questions and locations daily. Brand Performance uses a separate database and a weekly update schedule. Semrush’s data methodology
That distinction matters when you investigate a change. Suppose a brand’s broad research score rises while five questions in its custom panel remain unchanged. Both reports may be behaving as designed. The buyer should establish whether the question set, date range, refresh process or metric changed before attributing the difference to new content.
There is a documentation detail to resolve in a demonstration: the current methodology page describes rolling daily research updates in one section and monthly prompt-data updates in its summary. Ask which schedule applies to the report you will buy. Do not turn either line into a blanket promise about every view. The same methodology page
For a purchasing test, ask an operator to open one result from a report and trace it to its underlying question, answer, date and source. Then change the report’s location or dataset filter and inspect what changed. This reveals more about suitability than a screenshot of the headline score.
Ahrefs: decide between broad research and a custom panel
Ahrefs Brand Radar provides both broad AI-visibility research and custom prompt tracking. Its help documentation describes finding cited pages and domains, exploring competitors and filtering results. Broad research can help discover questions and sources you would have missed in a manually chosen panel. A custom panel lets you return to the same purchasing questions over time. Ahrefs’ Brand Radar overview
Keep the two datasets visible in reporting. Ahrefs documents a filter that can select its research prompts or your tracked prompts; leaving the filter unset combines them. A combined view may be useful for exploration. For an experiment, retain the frozen panel separately so a change in the surrounding dataset cannot quietly change the question you are measuring. Ahrefs’ custom-prompt documentation
Inspect each platform’s collection mode too. The current Brand Radar overview explicitly describes Claude tracking through an API with web search, available for custom prompts and consuming eight checks per execution. That should be labelled as the documented API mode when comparing it with observations from a consumer website. The documentation also reports a temporary inability to collect new Grok data. A provider name in a feature list needs a current availability and mode check. Ahrefs’ platform details
An API response can help test a model workflow. A consumer-search capture documents what appeared in that consumer surface under particular conditions. Preserve the collection mode when deciding which conclusion a result supports.
Where Beacon fits, and what it must demonstrate
Beacon has two separately priced offers. SaaS monitoring covers prompt tracking, share of voice and basic AI visibility reporting, with published monthly plans of $49, $99, $199 and $399. Confirm the exact surfaces, cadence, access and deliverables in a walkthrough. Enterprise and agency interactive assistant or plugin implementation is Custom: a separately scoped service for supported platforms such as ChatGPT and Claude. Availability, connection requirements, permissions, integration work and maintenance are agreed for each project. A monitoring subscription does not include a custom plugin build. Beacon pricing.
Beacon’s stated direction combines catalogue-grounded branded assistant implementation with monitoring. Its public material describes product-answer and agency workflows. Treat the proposed engagement as a concrete scope to verify, including supported assistants, catalogue access, review requirements and responsibility for corrections. Beacon’s public product description
For a catalogue project, the implementation scope should answer questions such as:
- Which product system supplies current variant, price, availability and warranty facts?
- How does the assistant choose the correct market and effective date?
- What happens when a source is missing, stale or contradictory?
- Does the experience require a connection, installation or explicit invocation?
- Who maintains the integration after a catalogue or platform change?
- Which actions can it perform, and which require the customer to continue elsewhere?
Require a demonstration of the workflow you are buying. An illustrative console, an industry brand example or a provider-directory reference cannot substitute for that demonstration.
This article does not claim that Beacon replaces a complete SEO research suite or that a connected assistant earns automatic recommendations in Google, ChatGPT or any other provider. A proposal can define implementation work and monitoring obligations. The provider-controlled appearance of a brand in an unconnected answer still needs its own evidence.
Compare a workload before comparing the price
Consider this illustrative procurement brief. It is not customer data or a statement about any vendor’s performance:
- 30 buyer questions
- Three specified answer surfaces
- Two locations
- Four scheduled runs during the month
That creates 720 planned question–surface–location observations: 30 × 3 × 2 × 4. If the same panel runs every day in a 30-day month, the count becomes 5,400. Extra validation repeats, retries and platform-specific weights may change billable consumption.
Those counts describe the work. Each supplier must explain how it maps that work to its own billing units.
What the published prices establish
| Purchase | Published detail checked for this article | What still needs matching to the brief |
|---|---|---|
| Semrush AI Visibility Base | The pricing page displays $99/month per domain, billed annually, with 25 custom prompts | Whether each question/location combination consumes a prompt; required extra domains, user access, prompts and billing term |
| Ahrefs custom tracking | Basic: US$50 for 2,500 checks; Growth: US$100 for 7,000 checks; Scale: US$250 for 25,000 checks | Platform weights, included allowances, overage settings and any other required product purchases |
| Ahrefs broad AI research | The overview lists US$199/month for a single AI index or US$699/month for all platforms | Which research indexes are useful beyond the custom panel and the current account requirements |
| Beacon SaaS monitoring / custom implementation | Published monitoring plans: $49, $99, $199 or $399 monthly. Enterprise/agency assistant and plugin builds: Custom, quoted separately | Exact monitoring surfaces, cadence, markets and access; a separate implementation scope, permissions, maintenance and acceptance test |
Sources: Semrush’s current pricing display, Ahrefs’ tracking prices and check definition, Ahrefs’ research purchases, Beacon’s published offer. Confirm the currency, tax and contractual term of the actual quote; the table does not turn a displayed monthly equivalent into a month-to-month commitment.
Ahrefs defines the ordinary check as one prompt execution, one model and one location. On that definition, the illustrative 5,400-check panel would cost US$108 on Basic if all observations use ordinary check weights and the published US$0.020 overage applies: US$50 plus 2,900 × US$0.020. Growth’s US$100 allowance would cover that count. This is arithmetic for that component, before other purchases, tax or changed usage; it is not a total subscription quote. Check units and overages
For Semrush, the illustrative brief already contains more distinct questions than the published base allowance of 25. Obtain a quote that states how the two locations and selected surfaces consume capacity. For Beacon, do the same with the proposed cadence and human review work. Avoid comparing one supplier’s daily run with another’s weekly report as though they deliver the same workload.
Run a demonstration that can change the buying decision
Use a fictional fixture or a product record you are authorized to share. For example, prepare a lamp record with a model identifier, Singapore price, warranty and effective date. Add a deliberately stale alternative record. These are test inputs, not claims that any vendor made an error.
Ask each supplier to handle the same six steps.
1. Preserve the input and the answer. The report should show the exact question, surface, time, location and collected answer. A collection failure needs a separate state. It should not become an absent-brand result.
2. Identify the correct entity. Test a similar company name and a differently spaced brand name. Check whether the system credits a namesake, parent company or unrelated product. A domain match and a brand-name match can answer different questions.
3. Inspect the product claim. Point to one price or warranty statement. Ask where the authoritative fact came from and whether its market and date match. A positive mention can still contain a wrong fact.
4. Inspect the link’s role. Ask the operator to show why a retained link is classified as a source citation. A resolved URL can be a navigational link or another kind of reference. Record what remains ambiguous.
5. Assign the correction. If a retailer page, manufacturer feed and brand page disagree, name the owner of each correction. Ask which changes the supplier will implement, which it will recommend and which depend on another organisation.
6. Recheck under comparable conditions. Preserve the panel and report missing results. Add new exploratory questions separately so a favourable new question does not overwrite the original test.
For an assistant implementation, add a seventh step: start a fresh session, establish the required connection and complete the intended task. Include one missing-data case and one action the assistant should refuse or hand off. Record the behavior, permissions and any downstream handoff.
This demonstration produces a concrete acceptance record. It also exposes work that a software subscription alone may leave with the buyer.
Put responsibility into the proposal
Ask for a short responsibility table alongside the price. For each deliverable, name who provides the data, who reviews it, who changes it and who owns the next measurement.
A catalogue accuracy engagement might assign product facts to the brand, website corrections to its web team, assistant integration to an implementation partner and independent discovery measurements to the research platform. An agency might perform several of those roles. The proposal should still name them separately so the client can see what is included.
Specify what happens when the assistant provider changes its interface, a data source becomes unavailable or a tracked question yields no answer. Also request an export example and a handover plan. A report the client can inspect and continue using is more valuable than an unexplained score.
If your team already owns Semrush or Ahrefs, test the relevant AI workflow inside that existing relationship before adding another subscription. If the uncovered gap is catalogue-connected implementation, request a demonstration and scoped proposal for that work. Take the same product fixture and workload brief into each conversation, then compare the evidence, recurring effort and responsibilities you would actually receive.