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Lusha

MARKETING
Velocity5.0

B2B contact intelligence and sales prospecting

www.lusha.com ↗

Lusha's feed is a content-marketing operation, not a changelog — but the research it publishes is unusually self-critical.

b2b-datacontent-marketingmcpagent-prospectingdata-accuracy
◆Current state
Every entry in this feed is a blog post, delivered as a truncated teaser with the body behind the link. No product release, version, or feature announcement appears anywhere in the recent window. What the posts cover is a running comparison of B2B data providers — Lusha against Apollo, ZoomInfo, and Cognism — plus a Lusha Labs experiment series testing whether AI agents can find contactable senior buyers without a verified data connector.
◆Where it's heading
The editorial line is a bet on agent-mediated prospecting. Several posts are explicitly about MCP servers — which vendors have actually exposed lookalike search and account research to Claude and ChatGPT rather than keeping them in their own UI — and one dissects how an agent picks a connector and burns credits invisibly. Lusha is arguing that the value is moving from the search box to the connector the agent calls, which is a positioning claim about where its own product needs to sit. The provider comparisons and the debunking of the industry's unsourced 30%-decay statistic are trust plays aimed at the same audience.
◆Prediction
Direction cannot be read from this feed with confidence — it carries no product releases. The content strategy points toward Lusha's MCP surface being the thing it wants judged, so any real announcement is likely to concern agent-facing access rather than the web app.

◆Recent moves

  1. 18d ago

    B2B data decay: what we measured against 148,000 records

    A blog post reporting that the industry-standard 30%-annual-decay figure has no traceable source, alongside Lusha's own measurement against 148,000 records. Editorial content in a marketing feed — no product change.

    View source ↗
  2. 18d ago

    Lusha Labs #03: The filter that hides the CRO

    Third post in the Lusha Labs series, testing across twenty companies how each added search filter narrows results and what it costs in credits. Research content, not a release.

    View source ↗
  3. 18d ago

    Lusha Labs #02: Why your search returned nothing

    Lusha Labs #02 re-runs the contactability comparison between public web research and a verified data connector on a fresh set of ten companies. Blog content supporting the feed's agent-prospecting argument.

    View source ↗
  4. 19d ago

    Lusha Labs #01: Can ChatGPT find accurate B2B contacts? We tested it

    The first Lusha Labs experiment, asking ChatGPT to identify senior sales leaders at ten B2B companies using public web research alone. Sets up the series' thesis about verified connectors; carries no product news.

    View source ↗
  5. 19d ago

    How AI agents pick your data tool, and where the credits actually go

    An explainer on how an agent silently chooses a data connector and spends credits on the user's behalf. Relevant to where Lusha is positioning itself, but it is a blog post rather than a change to the product.

    View source ↗
  6. 22d ago

    B2B data accuracy: how the major providers actually compare in 2026

    A comparison of published accuracy claims across Lusha, Apollo, ZoomInfo, and Cognism, leading with the observation that vendor accuracy numbers are not comparable. Competitive marketing content.

    View source ↗