Enrich inbound leads with a Lusha agent in Microsoft Copilot

Built by: Lusha
Time to build: 2 min
Difficulty: Easy
Tools: LushaMicrosoft Copilot
Type: Prompt

Example outputs in this play are illustrative — they reflect the structure, fields, and format of a Lusha-powered Copilot agent workflow, but were not pulled from a live session. Run the prompt with your own inbound leads and approved Lusha data sources to see live results.

Inbound leads often arrive with just enough information to create work.

A name. An email. A company field that may or may not be clean. A form answer. Maybe a source campaign. Before sales can act, someone still has to answer the real questions: Who is this person? What company are they connected to? Is the account a fit? Is there a signal that makes the timing stronger? Should this go to sales now, nurture, or review?

This prompt uses a Lusha GTM Data Agent in Microsoft Copilot to enrich inbound leads with verified contact and company data, check account fit, surface buyer signals, and recommend the next-best action. Instead of routing every form fill the same way, your team gets a cleaner handoff: who the lead is, why they matter, and what should happen next.

How to start

1

Open your Lusha GTM Data Agent in Microsoft Copilot

Use the Lusha GTM Data Agent you created in Microsoft Copilot. The agent should be connected to approved Lusha actions, APIs, MCP tools, or knowledge sources.

2

Paste your inbound lead list

Add the lead details you have: name, email, company, title, form source, campaign, and any form answers. The prompt works even when some fields are missing.

3

Send the prompt

The agent enriches each lead, checks account fit and buyer signals, then recommends whether to route to sales, nurture, review, or exclude.

The prompt

Use this with your Lusha GTM Data Agent in Microsoft Copilot.

Use Lusha to enrich these inbound leads and recommend
the next-best action for each one.

INBOUND LEADS:
Paste leads in this format:

1. [Full name] | [Email] | [Company] | [Title] |
   [Form source] | [Campaign] | [Form answer or note]
2. [Full name] | [Email] | [Company] | [Title] |
   [Form source] | [Campaign] | [Form answer or note]
3. [Full name] | [Email] | [Company] | [Title] |
   [Form source] | [Campaign] | [Form answer or note]

LEAD CONTEXT:
Source: [website form / webinar / demo request / content
download / event / partner / paid campaign / other]
Offer or conversion point: [demo / report / webinar /
trial / contact sales / consultation / other]
What the lead showed interest in: [one sentence]

ICP:
Best-fit industries: [industries]
Best-fit company size: [employee range]
Best-fit regions: [regions]
Target personas: [titles or personas]
Relevant departments: [Sales / Marketing / RevOps / IT /
Operations / Customer Success / Finance / HR / other]
Disqualifiers: [students, consultants, competitors, vendors,
existing customers, poor-fit segments, unsupported regions,
small companies, etc.]

MY PRODUCT:
[One sentence describing what you sell and the problem
it solves]

Using Lusha, do the following:

1. VERIFY EACH LEAD
   For each lead, verify whether the person can be matched
   to a real B2B contact profile.

   Return:
   - Name
   - Current title
   - Current company
   - Department
   - Seniority
   - Location
   - LinkedIn profile if available
   - Whether the submitted title and company match the
     verified profile

   Flag:
   - Personal email
   - Company mismatch
   - Title mismatch
   - Contact no longer at company
   - Contact outside target persona
   - Contact could not be verified

2. ENRICH CONTACT DATA
   For each verified lead, return:
   - Verified business email availability
   - Direct or mobile phone availability
   - DNC status if available
   - Last updated date if available

   If contact data is unavailable or cannot be revealed,
   say so clearly rather than guessing.

3. ENRICH COMPANY DATA
   For each lead’s company, return:
   - Company name
   - Domain
   - Industry
   - Employee count
   - HQ location
   - Revenue range if available
   - Tech stack if available
   - Company LinkedIn if available

4. CHECK BUYER SIGNALS
   Check recent buyer signals from the last 6 months,
   if available.

   Prioritize:
   - Funding events
   - Hiring growth
   - Hiring growth by relevant department
   - Hiring growth by location
   - Leadership changes
   - Role changes
   - Company changes
   - Headcount growth or reduction
   - Technology changes
   - Website traffic changes
   - Commercial activity news
   - Corporate strategy news
   - Product activity news
   - Risk news
   - Intent topics related to my product, if available

5. SCORE AND PRIORITIZE
   Create an explainable recommendation score from 1-100
   using only the verified Lusha data returned and the ICP
   context I provided.

   Break the score into:
   - Contact fit: 25 points
     How well the person matches the target persona.

   - Company fit: 30 points
     How well the company matches the ICP.

   - Timing: 25 points
     Whether buyer signals make the lead more timely.

   - Actionability: 20 points
     Whether verified contact data is available and usable.

   Do not present the score as a prediction that the lead
   will convert or buy.

   If there is not enough verified data to support a score,
   mark the confidence as low and explain what is missing.

6. RECOMMEND ROUTING
   Assign one next-best action:

   Route to AE now:
   Strong contact fit + strong company fit + strong signal
   or high-intent form source.

   Route to SDR:
   Good fit, but needs qualification before AE handoff.

   Add to nurture:
   Partial fit, weak timing, junior title, or unclear urgency.

   Review manually:
   Data mismatch, personal email, unclear company, or
   incomplete verification.

   Exclude:
   Competitor, vendor, student, poor fit, unverified, or
   disqualified.

7. WRITE FOLLOW-UP COPY
   For leads marked Route to AE now or Route to SDR, write
   one short follow-up email.

   Subject line:
   Under 7 words.

   Body:
   Under 100 words.
   Reference the conversion point or stated interest.
   Connect the message to the strongest company or buyer
   signal when available.
   End with one clear, low-friction next step.

   For nurture leads, write one nurture angle instead.
   For review or exclude leads, do not write sales follow-up.

   Do not:
   Invent form answers, attendance, pain points, signals,
   tools, vendors, internal projects, buying intent, emails,
   phone numbers, or company context.
   Say the lead is ready to buy.
   Claim a signal proves intent.
   Use the same generic follow-up for every lead.

8. OUTPUT FORMAT
   Return:
   - Lead enrichment table
   - Verification status
   - Contact data availability
   - Company enrichment
   - Buyer signals, if any
   - Recommendation score and confidence
   - Routing recommendation
   - Follow-up email or nurture angle
   - Review and exclusion reasons

If Lusha cannot verify a lead, company, contact detail, or
signal, mark it clearly rather than guessing.

What you’ll get back

 

A prioritized inbound lead list with verified contact data, company enrichment, buyer signals, routing recommendations, and follow-up copy. Here’s what the output looks like:

Inbound lead enrichment — Lusha agent

FieldValue
Leads reviewed25 submitted · 19 verified · 4 review · 2 exclude
Top leadR.M. · VP Revenue Operations · verified business contact
Company fitStrong ICP fit · B2B SaaS · 500–1,000 employees
Strongest signalHiring growth in RevOps · supports workflow automation angle
RoutingRoute to AE now · high fit + timely signal + contact data available
Follow-upShort email included · conversion point + signal-based angle

Example outputs in this play are illustrative — they reflect the structure, fields, and format of a Lusha-powered Copilot agent workflow, but were not pulled from a live session. Run the prompt with your own inbound leads and approved Lusha data sources to see live results.

 

Why use a Lusha agent in Copilot for inbound lead enrichment

 

Inbound leads should not all be treated the same. A senior buyer at a strong-fit account with recent hiring growth deserves a different next step than a junior contact from a poor-fit company with no verified business data.

A Lusha GTM Data Agent helps Copilot turn raw lead submissions into a more useful sales handoff. The agent can verify the contact, enrich the company, check buyer signals, and recommend whether the lead should go to an AE, SDR, nurture, review, or exclusion path.

The signal layer matters because form intent is only part of the story. A demo request may be strong on its own, but a verified buyer at a company showing relevant hiring growth or leadership change gives sales a better reason to act quickly. On the other hand, a content download from a poor-fit or unverified lead may belong in nurture instead of immediate sales follow-up.

The result is a cleaner inbound workflow: verified data, clearer prioritization, better routing, and more relevant follow-up.

Lusha data is sourced and used in accordance with Lusha’s Privacy Policy and Terms of Use. Lusha is GDPR compliant and covers contacts across North America, EMEA, and APAC.

FAQ

  • Can I use this for demo requests and content downloads?

    Yes. Add the lead source and conversion point in the prompt. The agent can use that context along with Lusha enrichment, company fit, and buyer signals to recommend the right next step.

  • What if a lead used a personal email address

    The prompt asks the agent to flag personal emails and verify whether the person can be matched to a business contact. If the lead cannot be verified, it should be marked for review instead of routed automatically.

  • Does this replace lead scoring in my CRM?

    No. This prompt can support lead scoring and routing decisions, but it should not replace your CRM rules or RevOps process. Use it to enrich, explain, and prioritize leads before handoff.

  • What if Lusha finds no buyer signals?

    A lead can still be worth following up with if the contact and company fit are strong. Signals help prioritize timing, but fit, source, and contact availability still matter.

  • Can this help sales and marketing align on lead quality?

    Yes. The output gives both teams the same view of contact verification, company fit, buyer signals, routing recommendation, and follow-up angle.

Ready to run this?

One data connection. Works in Claude, ChatGPT, your CRM, or any agent you build.