Build vs Buy SERP API: ROI Calculator & 12-Month TCO

TL;DR

Most engineering teams start by assuming they can build a SERP scraper themselves. It seems simple at first, but once you factor in maintenance, proxies, anti-bot handling, and support for different engines and locations, the build vs buy SERP API question becomes more complex. Over 12 months, building in-house often becomes 3–5 times more expensive than using a managed SERP API.

There is also a major time difference. An API can be integrated in a day, while an internal scraper usually takes a few months to build and stay stable. During that time, engineering is focused on infrastructure instead of revenue features. This is where the opportunity cost becomes clear.

If you are evaluating in-house development versus a ready-to-use SERP API, this article gives you the key SERP API ROI insights and a calculator to model the numbers for your own platform.

Let’s dive in!

The Hidden Costs of Building a SERP Scraper In-House

Many teams budget only for the initial development effort, but the long-term cost of running and maintaining a production-grade SERP scraper is far higher than it first appears.

These hidden costs listed below accumulate quickly and often exceed the original estimate within the first year.

Initial development time: Building a stable scraper requires more than writing extraction code. It involves browser automation, rendering, proxy routing, and building support for multiple engines and regions.
Proxy infrastructure and bandwidth: To collect SERP data reliably, teams need a rotating pool of quality proxies, region targeting, bandwidth, and ongoing IP replacement. These quickly become monthly recurring expenses.
Anti-bot countermeasures: Search engines update detection methods regularly. Engineering must adapt fingerprints, headers, device profiles, and retries to avoid blocks and CAPTCHAs.
Support for multiple engines and markets: Each new engine or geography requires separate parsing logic and testing. Maintaining parity across them becomes an ongoing project.
Maintenance burden: Google, Bing, and other engines regularly change their HTML structure, query parameters, and result formatting, forcing scrapers to update their logic. For example, Google has deprecated parameters such as num=100 that once returned 100 results per query.
Quality assurance and monitoring: Scrapers require continuous checks for accuracy, latency, failure rates, and data freshness. This adds monitoring systems and manual QA time to the workload.

Operational Risks of Building In-House SERP APIs

Even internally well-built SERP APIs reach a point where maintenance becomes a constant responsibility. These are the areas where teams usually start feeling the gap between an in-house system and a managed SERP solution.

Frequent search engine changes: Google, Bing, and others update layouts and structures without warning, which can break parsing logic instantly and require rapid fixes.
Evolving bot detection systems: Engines now rely on fingerprinting, device signals, and dynamic challenges that require continuous adjustment to avoid blocks.
Complexity across engines and markets: Each search engine and region uses different structures, languages, and result formats, adding layers of logic to maintain.
Higher expectations for reliability: Meeting strong uptime and accuracy standards demands constant monitoring of success rates, latency, and error patterns.
Incident and recovery overhead: Every outage or accuracy drop interrupts engineering work, and recovery can take days or weeks, depending on the source of the change.

Time to Market Comparison

Time to market is often the biggest practical difference between building a SERP scraper and using a managed SERP API. An API can go live almost immediately, while an in-house build requires months of engineering work and ongoing upkeep.

The table below shows the contrast at a glance.

Building In-House	Using Bright Data SERP API
3–6 months to build a stable scraper that handles rendering, retries, proxy routing, and parsing	Get started in minutes with ready-to-use API requests and code examples.
Requires continuous updates whenever search engines change their structure	Updates handled by Bright Data with no engineering effort
Engineering must maintain proxy pools, anti-bot flows, and browser logic	No infrastructure to maintain, API manages unblocking and proxy rotation
Longer launch timelines delay product features and revenue opportunities	Faster launch allows teams to ship features sooner and stay competitive

Calculate Your 12 Month TCO

This calculator estimates your 12-month cost of building a SERP scraper compared with using a managed SERP API. Enter your engineering costs, time to build, infrastructure spend, proxy costs, maintenance expectations, and monthly request volume.

The tool then shows your projected TCO, break-even point, and the expected savings at your scale. Use it to model your own numbers and see how the build vs buy SERP API changes as volume grows.

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<head>

<meta charset="utf-8" />

<meta name="viewport" content="width=device-width,initial-scale=1" />

<title>Build vs Buy SERP API - 12 Month TCO Calculator</title>



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<body>



<div class="container">

  <h1>Build vs Buy SERP API: 12-Month TCO Calculator</h1>



  <div class="grid">

    <!-- LEFT: inputs -->

    <div class="card left">

      <div class="section-title">Engineering Inputs</div>



      <label>Number of Engineers (FTE)

        <span class="info" data-tip="How many dedicated engineers will build the scraper? Minimum 1.">i</span>

      </label>

      <input id="fte" type="number" min="1" step="1" value="3">



      <label>Annual Salary per Engineer ($)

        <span class="info" data-tip="Enter fully loaded annual base salary. Use local currency if needed.">i</span>

      </label>

      <input id="salary" type="number" min="30000" step="1000" value="140000">



      <label>Months to Build

        <span class="info" data-tip="Estimated calendar months to reach stable production scraper. Typical 3–6 months.">i</span>

      </label>

      <input id="months" type="number" min="1" max="12" step="1" value="5">



      <label>Burden Multiplier (benefits, taxes)

        <span class="info" data-tip="Multiplier to account for employer taxes and benefits. Default 1.25">i</span>

      </label>

      <input id="burden" type="number" min="1" step="0.01" value="1.25">



      <div style="height:12px"></div>



      <div class="section-title">Infrastructure & Proxy</div>



      <label>Infra Cost per Month ($)

        <span class="info" data-tip="Monthly hosting, headless browser renderers, queues, storage.">i</span>

      </label>

      <input id="infra" type="number" min="0" step="100" value="2000">



      <label>Proxy / Bandwidth Cost per Month ($)

        <span class="info" data-tip="Self-managed proxy pool costs (residential/datacenter/ISP).">i</span>

      </label>

      <input id="proxy" type="number" min="0" step="100" value="8000">



      <div style="height:12px"></div>



      <div class="section-title">Maintenance & Failure</div>



      <label>Maintenance Rate (% of annual dev cost)

        <span class="info" data-tip="Percent of initial fully-loaded dev cost assumed for yearly maintenance. Typical 25–40%.">i</span>

      </label>

      <input id="maint" type="number" min="0" max="100" step="1" value="30">



      <label>Failure / Incident Hours per Month

        <span class="info" data-tip="Average engineering hours lost per month to fixes, regressions, and incidents.">i</span>

      </label>

      <input id="failHours" type="number" min="0" step="1" value="10">



      <div style="height:12px"></div>



      <div class="section-title">API Cost (Buy option)</div>



      <label>API Cost Method

        <span class="info" data-tip="Pick monthly spend or per-success pricing method.">i</span>

      </label>

      <select id="apiMethod" aria-label="API cost method">

        <option value="monthly" selected>Monthly API Spend</option>

        <option value="per">Per-success × Volume</option>

      </select>



      <label id="label-api-month">Monthly API Spend ($)

        <span class="info" data-tip="Enter the monthly fee you expect to pay for a managed SERP API (or Bright Data tier).">i</span>

      </label>

      <input id="api" type="number" min="0" step="1" value="10000">



      <label id="label-volume">Monthly Query Volume

        <span class="info" data-tip="Total monthly successful requests your product needs (used for per-success pricing).">i</span>

      </label>

      <input id="volume" type="number" min="0" step="1" value="100000" disabled>



      <label id="label-per-success">API Cost per Successful Request ($)

        <span class="info" data-tip="Per-success price in $ (e.g., 0.0005). Used when Per-success method is selected.">i</span>

      </label>

      <input id="perSuccess" type="number" min="0" step="0.00001" value="0.0005" disabled>



      <div id="validationErrors" class="error" style="display:none"></div>



      <button id="calcBtn" class="calc-btn" onclick="onCalculate()">Calculate 12-Month TCO</button>

    </div>



    <!-- RIGHT: outputs -->

    <div class="card right">

      <div style="display:flex;justify-content:space-between;align-items:center">

        <div class="section-title">Results</div>

        <div class="muted" style="font-size:13px">All values shown in USD</div>

      </div>



      <div class="result" aria-live="polite">

        <div class="muted">12-Month Build TCO:</div>

        <div style="font-size:18px;font-weight:600;margin-top:6px"><strong id="buildTCO">$0</strong></div>

      </div>



      <div class="result" aria-live="polite">

        <div class="muted">12-Month Buy TCO:</div>

        <div style="font-size:18px;font-weight:600;margin-top:6px"><strong id="buyTCO">$0</strong></div>

      </div>



      <div class="result">

        <div class="muted">Build is</div>

        <div style="font-size:18px;font-weight:600;margin-top:6px"><strong id="ratio">0x</strong> more expensive</div>

      </div>



      <div class="result">

        <div class="muted">Break-even Time</div>

        <div style="font-size:18px;font-weight:600;margin-top:6px"><strong id="breakeven">0 months</strong></div>

      </div>



      <div class="result">

        <div class="muted">Total Savings (12 months)</div>

        <div style="font-size:18px;font-weight:600;margin-top:6px"><strong id="savings">$0</strong></div>

      </div>



      <div class="chart-wrap">

        <canvas id="tcoChart" aria-label="Bar chart comparing build vs buy tco" role="img"></canvas>

      </div>

    </div>

  </div>

</div>



<script>

  // Utility to format currency

  function fmt(v){ return '$' + Number(v).toLocaleString(undefined, {maximumFractionDigits:0}); }

  function fmtFrac(v){ return '$' + Number(v).toLocaleString(undefined, {maximumFractionDigits:2}); }



  // [Chart.js](https://Chart.js) instance

  let tcoChart = null;



  // DOM refs

  const apiMethodEl = document.getElementById('apiMethod');

  const apiEl = document.getElementById('api');

  const volumeEl = document.getElementById('volume');

  const perSuccessEl = document.getElementById('perSuccess');



  const labelApiMonth = document.getElementById('label-api-month');

  const labelVolume = document.getElementById('label-volume');

  const labelPerSuccess = document.getElementById('label-per-success');



  const errorsEl = document.getElementById('validationErrors');



  // Toggle inputs based on selected API method

  function refreshApiMethodUI(){

    const method = [apiMethodEl.value](https://apiMethodEl.value);

    if(method === 'monthly'){

      [apiEl.disabled](https://apiEl.disabled) = false;

      [volumeEl.disabled](https://volumeEl.disabled) = true;

      [perSuccessEl.disabled](https://perSuccessEl.disabled) = true;

      [labelApiMonth.style.opacity](https://labelApiMonth.style.opacity) = '1';

      [labelVolume.style.opacity](https://labelVolume.style.opacity) = '0.6';

      [labelPerSuccess.style.opacity](https://labelPerSuccess.style.opacity) = '0.6';

    } else {

      [apiEl.disabled](https://apiEl.disabled) = true;

      [volumeEl.disabled](https://volumeEl.disabled) = false;

      [perSuccessEl.disabled](https://perSuccessEl.disabled) = false;

      [labelApiMonth.style.opacity](https://labelApiMonth.style.opacity) = '0.6';

      [labelVolume.style.opacity](https://labelVolume.style.opacity) = '1';

      [labelPerSuccess.style.opacity](https://labelPerSuccess.style.opacity) = '1';

    }

    // clear previous errors

    [errorsEl.style.display](https://errorsEl.style.display) = 'none';

    [errorsEl.innerText](https://errorsEl.innerText) = '';

  }



  apiMethodEl.addEventListener('change', refreshApiMethodUI);

  refreshApiMethodUI();



  // Validation function, returns array of errors (empty = valid)

  function validateInputs(values){

    const errs = [];



    if(!Number.isFinite(values.E) || values.E < 1) errs.push('Engineers must be at least 1.');

    if(!Number.isFinite(values.S) || values.S < 30000) errs.push('Salary must be at least 30,000.');

    if(!Number.isFinite(values.M) || values.M < 1 || values.M > 24) errs.push('Months to build must be between 1 and 24.');

    if(!Number.isFinite(values.B) || values.B < 1) errs.push('Burden multiplier must be at least 1.');

    if(!Number.isFinite(values.I_month) || values.I_month < 0) errs.push('Infra monthly cost must be 0 or greater.');

    if(!Number.isFinite(values.P_month) || values.P_month < 0) errs.push('Proxy monthly cost must be 0 or greater.');

    if(!Number.isFinite(values.Maint_pct) || values.Maint_pct < 0 || values.Maint_pct > 1) errs.push('Maintenance rate must be between 0% and 100%.');

    if(!Number.isFinite(values.failHours) || [values.failHours](https://values.failHours) < 0) errs.push('Failure hours must be 0 or greater.');



    if(values.method === 'monthly'){

      if(!Number.isFinite(values.API_month) || values.API_month <= 0) errs.push('Monthly API spend must be greater than 0 when using Monthly API Spend method.');

    } else {

      if(!Number.isFinite(values.volume) || [values.volume](https://values.volume) <= 0) errs.push('Monthly query volume must be greater than 0 for per-success method.');

      if(!Number.isFinite(values.perSuccess) || [values.perSuccess](https://values.perSuccess) <= 0) errs.push('API cost per success must be greater than 0 for per-success method.');

    }



    return errs;

  }



  // Main calculate function

  function calculate(values){

    // salary calculations

    const salary_month = values.S / 12;

    const initial_dev_cost = values.E * salary_month * values.M;

    const fully\_loaded = initial\_dev\_cost \* values.B;



    // infra + proxy

    const infra\_annual = values.I\_month \* 12;

    const proxy\_annual = values.P\_month \* 12;



    // maintenance

    const maint\_annual = fully\_loaded \* values.Maint\_pct;



    // failure

    const hourly\_rate = salary\_month / 160;

    const failure\_annual = hourly\_rate \* [values.failHours](https://values.failHours) \* 12;



    // build TCO

    const buildTCO = fully\_loaded + infra\_annual + proxy\_annual + maint\_annual + failure\_annual;



    // buy TCO

    let API\_month = 0;

    if(values.method === 'monthly'){

      API\_month = values.API\_month;

    } else {

      API\_month = [values.volume](https://values.volume) \* [values.perSuccess](https://values.perSuccess);

    }

    const buyTCO = API\_month \* 12;



    // ratio and break-even

    const ratio = buyTCO > 0 ? buildTCO / buyTCO : Infinity;

    const breakeven = API\_month > 0 ? buildTCO / API\_month : Infinity;

    const savings = buildTCO - buyTCO;



    return {

      buildTCO, buyTCO, ratio, breakeven, savings, API\_month,

      breakdown: { fully\_loaded, infra\_annual, proxy\_annual, maint\_annual, failure\_annual }

    };

  }



  // Draw chart

  function drawChart(buildTCO, buyTCO){

    const ctx = document.getElementById('tcoChart').getContext('2d');

    if(tcoChart) tcoChart.destroy();



    const maxVal = Math.max(buildTCO, buyTCO) || 1;

    const suggestedMax = Math.ceil(maxVal \* 1.1 / 1000) \* 1000;



    tcoChart = new Chart(ctx, {

      type:'bar',

      data:{

        labels:\['Build TCO','Buy TCO'],

        datasets:\[{

          label:'12 Month Cost ($)',

          data:\[buildTCO, buyTCO],

          backgroundColor:\[ 'rgba(62,123,250,0.95)', 'rgba(175,198,230,0.95)' ],

          borderRadius:6,

          barThickness:48

        }]

      },

      options:{

        responsive:true,

        maintainAspectRatio:false,

        plugins:{

          legend:{display:false},

          tooltip:{

            callbacks:{

              label:function(context){

                const v = [context.raw](https://context.raw);

                return ' ' + fmtFrac(v);

              }

            }

          }

        },

        scales:{

          x:{ ticks:{ color: '#E8F3FF' }, grid:{ display:false } },

          y:{

            beginAtZero:true,

            suggestedMax: suggestedMax,

            ticks:{ color:'#E8F3FF', callback: function(v){ return v >= 1000 ? '$' + (v/1000) + 'k' : '$' + v; } },

            grid:{ color:'rgba(255,255,255,0.04)' }

          }

        }

      }

    });



    // Resize canvas container height to show bars nicely

    document.getElementById('tcoChart').[style.height](https://style.height) = '260px';

  }



  // Handler when calculate button clicked

  function onCalculate(){

    // gather inputs

    const method = [apiMethodEl.value](https://apiMethodEl.value);

    const values = {

      E: Number(document.getElementById('fte').value),

      S: Number(document.getElementById('salary').value),

      M: Number(document.getElementById('months').value),

      B: Number(document.getElementById('burden').value),

      I\_month: Number(document.getElementById('infra').value),

      P\_month: Number(document.getElementById('proxy').value),

      Maint\_pct: Number(document.getElementById('maint').value) / 100,

      failHours: Number(document.getElementById('failHours').value),

      method: method,

      API\_month: Number(document.getElementById('api').value),

      volume: Number(document.getElementById('volume').value),

      perSuccess: Number(document.getElementById('perSuccess').value)

    };



    // Validation

    const errs = validateInputs(values);

    if(errs.length){

      [errorsEl.style.display](https://errorsEl.style.display) = 'block';

      [errorsEl.innerText](https://errorsEl.innerText) = errs.join(' ');

      return;

    } else {

      [errorsEl.style.display](https://errorsEl.style.display) = 'none';

      [errorsEl.innerText](https://errorsEl.innerText) = '';

    }



    // calculate

    const res = calculate(values);



    // update UI

    document.getElementById('buildTCO').innerText = fmt(Math.round(res.buildTCO));

    document.getElementById('buyTCO').innerText = fmt(Math.round(res.buyTCO));

    document.getElementById('ratio').innerText = (res.ratio===Infinity? '—' : res.ratio.toFixed(2)+'x');

    document.getElementById('breakeven').innerText = (res.breakeven===Infinity? '—' : res.breakeven.toFixed(1)+' months');

    document.getElementById('savings').innerText = fmt(Math.round(res.savings));



    // chart

    drawChart(Math.round(res.buildTCO), Math.round(res.buyTCO));

  }



  // Initialize: wire up API method toggling

  function init(){

    apiMethodEl.addEventListener('change', refreshApiMethodUI);

    refreshApiMethodUI();

    // run initial calculation with defaults

    onCalculate();

  }



  init();

</script>



</body>

</html>

Real World Scenarios: A Practical SERP API Cost Comparison

When teams model their own situation, the cost difference between building a SERP scraper and using a managed solution becomes much clearer.

Below are three realistic scenarios drawn from what we commonly see across SEO SaaS companies, from early-stage teams to platforms operating at significant scale.

Scenario A — Startup Stage (around 10K requests per month)

This is typically a small team with one or two engineers who take on scraping as a side project. It works at first, but the cost picture tells a different story.

Inputs

E = 2 engineers
S = $120,000 annual salary
M = 4 months to build
B = 1.25 burden multiplier
I_month = $1,000 infrastructure
P_month = $2,000 proxies
Maint_pct = 30%
API_month = $5,000

Results

Build TCO (12 months): $166,000
Buy TCO (12 months): $60,000
Building is ~2.77 times more expensive
Break-even is 33 months, far beyond the first year

Even at low volume, the cost of building a SERP scraper climbs quickly once you include maintenance and proxy spend.

Scenario B — Growth Stage (around 100K requests per month)

This is where teams often start feeling the pain. More traffic means more breakage, more retries, and more time spent firefighting instead of shipping features.

Inputs

E = 3, S = $140,000, M = 5
I_month = $2,000, P_month = $8,000
Maint_pct = 30%, API_month = $10,000

Results

Build TCO: $404,375
Buy TCO: $120,000
Building costs ~3.37 times more than buying

At this stage, the gap between in-house systems and managed solutions becomes hard to ignore.

Scenario C — Scale Stage (1M+ requests per month)

Large platforms almost always underestimate how quickly complexity compounds. At this scale, reliability is essential, and maintenance becomes a full-time commitment.

Inputs

E = 4, S = $160,000, M = 6
I_month = $5,000, P_month = $30,000
Maint_pct = 35%, API_month = $20,000

Results

Build TCO: $960,000
Buy TCO: $240,000
Building is 4 times more expensive

This is where a clear SERP API cost comparison shows its value. Buying replaces a high-maintenance internal system with predictable, scalable costs.

Bright Data Cost: Transparent Per Success Pricing

Bright Data’s SERP API uses a pricing model that scales cleanly with usage, which makes cost forecasting far easier than maintaining an internal scraper. Here are the factors that matter when comparing this to the cost of building at different volumes:

You pay only for successful SERP results: Each API call is billed only when data is delivered, which removes wasted spend on failed or blocked attempts. This keeps costs aligned with real output, not inefficiencies.
Volume-based tiers support predictable scaling: Teams can model their SERP API expenses simply by projecting monthly request volume. This makes budgeting straightforward for both engineering and finance.
No infrastructure or proxy overhead: Internal systems require proxy networks, browser rendering, retries, and monitoring. With Bright Data, these costs disappear from your budget and operational planning.
Cost does not rise when search engines change: When SERP structures shift, Bright Data absorbs the maintenance work. Your cost remains stable, while internal systems face new development cycles.
Clear long-term economics: At every volume level, you can compare per-success pricing directly with the rising maintenance, infrastructure, and staffing requirements of an in-house scraper.

This transparency makes it easier for leaders to evaluate the true ROI and understand where a managed API becomes more efficient than building internally.

Opportunity Cost: What Your Engineering Team Could Build Instead

Cost is only one part of the build vs buy SERP API decision. The larger impact comes from how your engineering team uses its time. Every hour spent fixing a broken parser, managing proxies, or responding to anti-bot blocks is an hour not spent improving your product. When SERP collection moves to a managed API, those hours shift back toward work that has a direct customer and revenue impact.

Freed from scraper maintenance, teams can focus on features that help the business grow, such as richer SERP analytics, smarter ranking insights, or onboarding improvements that reduce churn. They can invest in productivity tools that speed development, refine the core user experience, or build capabilities that differentiate the platform from competitors.

Build vs Buy SERP API - Decision Checklist for CTOs

The table below summarizes the considerations that matter most for engineering teams making a long-term decision.

Building In-House is Good When…	Buying a Managed SERP Solution Is Optimal When…
SERP collection is a core product differentiator and part of your competitive moat.	SERP data is a commodity input rather than a unique value driver.
You need deeply customized enrichment, ranking, or proprietary logic that cannot be outsourced.	You want rapid time to market and minimal infrastructure overhead.
Your engineering team has surplus bandwidth and can support long-term internal ownership.	Predictable, stable costs matter more than building internal scraping systems.
You expect extremely high, sustained volumes that justify multi-year internal investment.	Reliability and bot detection management should be handled by a dedicated provider.
Ongoing maintenance, refactoring, and break/fix cycles fit your strategic roadmap.	You want engineering focused on core product value instead of maintaining scrapers.

What Bright Data Customers Say

“We spent $120K building, wish we used the API from day one,” says Alex R., Engineering Lead at a mid-market SEO platform. “Our in-house scraper worked, but the ongoing maintenance quickly became a full-time job. Switching to Bright Data’s SERP API finally gave our team back the time to focus on product development.”

Key Takeaways

Building an in-house SERP scraper becomes 3–5× more expensive over 12 months once you account for engineering time, maintenance, proxies, and scaling.
A managed SERP API provides predictable per success pricing and removes the ongoing effort of maintaining scrapers across engines and geographies.
The real ROI comes from redirecting engineering time toward revenue features and product improvements instead of constant scraper maintenance.

Get Started with a Data-Driven Decision

You can model your own numbers using the SERP API TCO calculator and see how the build vs buy SERP API plays out for your platform.

If you want to explore the API, you can test it with a free trial and review pricing options that match your scale.

Build vs Buy SERP API: ROI Calculator & 12-Month TCO

TL;DR

The Hidden Costs of Building a SERP Scraper In-House

Operational Risks of Building In-House SERP APIs

Time to Market Comparison

Calculate Your 12 Month TCO

Real World Scenarios: A Practical SERP API Cost Comparison

Scenario A — Startup Stage (around 10K requests per month)

Scenario B — Growth Stage (around 100K requests per month)

Scenario C — Scale Stage (1M+ requests per month)

Bright Data Cost: Transparent Per Success Pricing

Opportunity Cost: What Your Engineering Team Could Build Instead

Build vs Buy SERP API - Decision Checklist for CTOs

What Bright Data Customers Say

Key Takeaways

Get Started with a Data-Driven Decision

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Build vs Buy SERP API: ROI Calculator & 12-Month TCO

TL;DR

The Hidden Costs of Building a SERP Scraper In-House

Operational Risks of Building In-House SERP APIs

Time to Market Comparison

Calculate Your 12 Month TCO

Real World Scenarios: A Practical SERP API Cost Comparison

Scenario A — Startup Stage (around 10K requests per month)

Scenario B — Growth Stage (around 100K requests per month)

Scenario C — Scale Stage (1M+ requests per month)

Bright Data Cost: Transparent Per Success Pricing

Opportunity Cost: What Your Engineering Team Could Build Instead

Build vs Buy SERP API - Decision Checklist for CTOs

What Bright Data Customers Say

Key Takeaways

Get Started with a Data-Driven Decision

Last Week in Plain English

Interested in Promoting Your Content?

Help us expand the developer universe!