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See who AI recommends before the rate quote.

Track the questions that put lenders and brokers on a borrower's shortlist. Diagnose the market, loan type, branch, source and claim behind every answer.

See every shortlist you’re on.

Buyers ask the same thing a hundred ways, and each question gets its own picks. Track the questions that matter and see how far you are from the top.

First-home lenders

Haldacre Lending 4th, in 14 of 40

FHA or conventional

Haldacre Lending 1st, in 37 of 40

Self-employed buyers

Haldacre Lending 2nd, in 31 of 40

Refinance costs

Haldacre Lending 2nd, in 30 of 40

Investment loans

Haldacre Lending 4th, in 21 of 40

  • Haldacre Lending
  • Rivals
  • Your gap to first

40 AI answers per question. Height shows how many named each brand.

Explore the evidence

Give AI a reason to pick you.

Trakkr reads the pages behind every pick. When AI can’t find what it needs, Trakkr writes the fix and ships it once you approve.

  • You approve every change
  • Ships to Shopify, WordPress, Webflow and GitHub
Keyrith Mortgage

Raleigh first-time buyers

38of 40

Why AI picks it

  • Shows first-buyer stepsKeyrith Mortgage website
  • Explains application feesKeyrith Mortgage guide
ChatGPT says

“Shows each step for a first-time buyer.”

Fix ready1 of 3
haldacre-lending.test

List first-buyer steps and fees.

Haldacre Lending

First-home loans

14of 40
  • First-buyer fees are not explained.Haldacre Lending website

Follow every pick to your site.

Connect Google Analytics to see AI referral visits and landing pages. Recorded conversions depend on the events and values configured in your property.

30 days · AI referral visits

First-home loans

/first-home-loans
200 visits
200 AI visitsFixed

First-home lenders

/first-home-lenders
126 visits
126 AI visits

FHA or conventional

/fha-or-conventional
121 visits
121 AI visits

Self-employed buyers

/self-employed-buyers
77 visits
77 AI visits

AI referral visits

30-day total
524 visitsFour landing pages · AI referrals

Mini bars show 30 days of AI visits.

Google Analytics attribution

The buyer asks before your rate page loads.

AI discovery can create the consideration set, then send the borrower to a lender, broker, comparison or official source.

01

The answer forms a shortlist

A borrower can ask for a lender, broker or comparison before visiting a lender site. The answer decides which names deserve a closer look.

02

The same prompt changes by context

First-time buyer, self-employed, refinance, investment-property and programme questions need separate market and product views.

03

The sources must agree

Official guidance, licence records, lender education, disclosures, calculators, directories, reviews and community sources can support or weaken the same answer.

04

The next step must be approved

Growth needs a clear opportunity. Compliance needs the observed claim, source and surface. Branch teams need the exact market gap.

Open the full readout.

Switch views to see how Trakkr breaks down visibility for mortgage lenders and brokers, from the market to the work that moves it.

Haldacre Lending

Roll up the signal without hiding the branch.

See the executive number, then split it by borrower, loan type, state and local market.

AI shortlist visibility
61.4
−2.7 points over 30 days
Prompt wins
42 / 113
Across five borrower groups
Regulated citation share
38.6%
Official or licence sources
Claims to review
7
Rate, fee or eligibility language

First-time buyers

FHA · Raleigh-Durham, NC

68.3

+3.2

Branch education page lacks a clear Loan Estimate next step.

Self-employed borrowers

Conventional · Tampa Bay, FL

43.8

-6.1

Documentation guidance is thin and differs by branch.

Rate-term refinance

Conventional · Dallas-Fort Worth, TX

57.1

-1.9

Low closing-cost language is not aligned across surfaces.

Property investors

Investment property · Seattle, WA

54.9

+0.4

The calculator is useful, but local comparison proof is weak.

VA-eligible borrowers

VA · Colorado Springs, CO

71.2

+1.7

One branch page does not link back to current official guidance.

State and branch map

35 locations across five markets

Visibility by local prompt set
WASeattle5 locations · Investment property54.9+0.4
COColorado Springs4 locations · VA71.2+1.7
TXDallas-Fort Worth11 locations · Refinance57.1-1.9
FLTampa Bay8 locations · Self-employed43.8-6.1
NCRaleigh-Durham7 locations · First-time buyer68.3+3.2
View 1 of 5

Keep every observation in its market and lending context.

A useful measurement preserves the engine, date, prompt, borrower situation, loan type, place, claim and source.

  1. 01Define the question set

    Group real discovery prompts by borrower situation, loan type, state, branch and journey stage.

  2. 02Observe each answer

    Record the engine, date, recommendation position, peers, claims and cited sources.

  3. 03Separate signal from advice

    Measure what the answer says without calculating a rate, assessing eligibility or giving a borrower recommendation.

  4. 04Trace the evidence gap

    Connect a lost prompt to the page, disclosure, calculator, local fact, review theme or trusted source behind it.

  5. 05Route approved work

    Give growth, compliance and branch teams a specific action with its source and observed prompt attached.

Every answer and figure in the examples on this page is made up to show how Trakkr works, including those for real brands. The other company names are made up too.

Questions, answered.

What teams need to know before they track AI discovery.

No. Trakkr observes whether an AI answer makes a rate, fee, savings, eligibility or approval claim and records the supporting source. It does not calculate a rate, assess a borrower, predict approval or provide personalised lending advice.

Ask anything elseAsk anything else

The Agent answers from our docs, methods and pricing, and links to the source.

Be the pick.

Add your website and the questions your buyers ask. Track the answers, inspect the evidence and decide which changes to make.

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Check your site

Every question your buyers askchecked daily in eight AI models