How to Build Your Own DSP and Is It Even Worth It?

The idea of “building your own DSP” has been a Holy Grail of digital advertising for quite some time. Your own product puts you in the major leagues of Google, Amazon, and Trade Desk, gives absolute business freedom, and allows you to generate profits without mark-ups. Sounds like a dream, even when you take blood, sweat, and tears needed to achieve it.

The question is: how much blood, sweat, and tears? How much money? How many hours? And is it even worth it, or are there better alternatives? Building your own DSP is NOT easy, but it’s not impossible either. Time to find out how!

What Does Building a DSP Mean?

Firstly, we’ll settle the basics. What’s a DSP?

A demand-side platform (DSP) is an automated ad tech platform made for purchasing digital ad inventory programmatically through a real-time bidding protocol (RTB), as well as creating, managing, and optimizing programmatic ad campaigns.

In simple terms, a DSP is a platform for the demand side (advertisers, ad agencies, ad networks) of programmatic advertising that allows them to buy ad placements automatically.

But you already know all of that, don’t you?

Instead of further dissecting how programmatic advertising works, let’s analyze the moving parts of a DSP, a.k.a., things you’ll need to develop if you want to build your own.

Technically, a standard demand-side platform (DSP) includes several key components:

• Bidder

An algorithm-driven engine that evaluates ad impressions and places bids to buy ad inventory in milliseconds based on targeting options

• Ad Serving Engine

Basically, an ad server (in its primitive meaning) to store, host, and deliver creatives.

• User interface (UI)

A dashboard for campaign setup, management, and optimization

• Reporting toolset

Analytics tools providing real-time performance metrics, customizable dashboards, and first/third-party data visualization on KPIs like impressions, clicks, and conversions

• Integration tools

APIs that allow connecting with multiple ad exchanges, supply-side platforms (SSPs), data management platforms (DMPs), and verification tools for inventory access, audience data, and compliance.

3 Methods to Own a DSP

Building your own DSP implies creating a ready-to-use solution that consists of these elements. You develop all of these components in-house: coding the bidding algorithms, UI, databases, and integrations yourself, as well as hiring an internal programmatic team to run it smoothly.

This differs from buying a DSP, where you essentially subscribe to an already established third-party DSP and pay markups for its services. You don’t need to develop anything, the tech is already there, but naturally, you don’t have the same level of freedom over the product.

The branding and domain names also belong to the provider, so if you’re an ad network, this kind of hurts the brand image.

However, some DSP providers allow you to use their platform and brand it completely as your own. This is called white-labeling, and that’s what Epom and quite a few modern DSP providers do. In short, this is a middle ground between the shackles of a standard DSP and the obligations that come with an in-house solution.

There’s also outsourcing. This one should be obvious: instead of advertising themselves, brands simply outsource all of their activities to an ad agency. Basically, brands “leave everything to the pros.”

We’ll return to these alternative methods later in (and during) the article. For now, let’s concentrate on building your own DSP.

Building Your Own DSP: Where the Industry Is Heading

Our loyal readers remember that we’ve already discussed in-house programmatic buying in our blog. Why do we do this again? Well, let’s just say things have changed since 2023.

This time, only IAB came up with comprehensive research, so we won’t have a divergence in data.

Preludes aside, according to the latest IAB’s “Attitudes to Programmatic Advertising Report”, in 2024, 44% of advertisers still rely primarily on outsourcing for programmatic operations, and that’s the single largest share.

As for in-housing, its glory days are left in the COVID era.

It’s not all doom and gloom, though. 42% of the advertisers said they were planning to bring programmatic buying in-house by the end of 2025. Interestingly, even among these, 100% say they would use an external consultant for strategic guidance, and 80% confirm they already have the budget and resources to invest in the required technology and staff.

We’re not here to talk about SSPs, but there’s some peculiar data to think about: in 2022, the amount of publishers using an in-house solution for programmatic buying accounted for 39%; now it’s 59%.

What are the reasons behind all of these shifts? To understand that, we need to dive into what makes in-housing both perspective and frustrating.

Benefits of Building a DSP

The benefits of in-housing a DSP aren’t a secret. These include:

Full Control and Confidence

An in-house DSP gives you control over the entire platform. You can implement unique bidding algorithms, custom audience segments, or integrations and measure campaigns exactly as needed.

You capture all performance data directly and can dramatically change campaign settings, knowing full well your data is accurate.

No Markups and Middlemen

You are the one in control, and you are the head of all operations. That means there is nobody to charge you with their markups, complicate the processes, or underdeliver without explanations.

Some of our partnering agencies note:

“owning the code lets us deploy innovations as quickly as possible and avoid paying any external “take rate” on media buys”

Moreover, all intellectual property belongs to you, so you can easily white-label the resulting tech as a new product line.

Long-Term Investment

Although expensive upfront, an owned DSP eliminates ongoing agency or platform fees. Over time, especially at very high spend levels and if you do everything right, this will pay off.

At the peak of in-housing popularity (2019-2021), Bayer reported saving about 010–11 million in six weeks after moving programmatic buying fully in-house. In theory, each ad impression purchased via your own DSP incurs no middleman margin, resulting in a gradually higher ROI.

And once again, you are not limited to internal use. If your product is good, you can develop it as a SaaS.

Data and Security

All targeting and performance data stay within your organization. You avoid giving raw customer data to outside platforms. You don’t question where this data comes from and if it’s even legal.

This is increasingly valuable under privacy regulations like GDPR/CCPA: with your own DSP, you can enforce compliance directly and reduce the risk of third-party misuse.

Drawbacks of Building a DSP

The barriers to building your own DSP can be summed up in three words: money, time, and talent.

Let’s discuss each of the most popular questions people ask on these:

How Much Does It Cost to Build Your Own DSP?

The question you’ve been asking yourself for this whole article: “How much does building your own cost?” Well, as in many things in ad tech, it depends.

On average, building a DSP from scratch is a multi-year engineering project costing on the order of $1.5–2.5 million per year at a minimum. That estimate includes salaries, servers, cloud resources, data storage, maintenance, and ongoing development.

For example, storing campaign data might reach ~$3,500/month (>$40k/year). Unless your digital ad budget is very large (estimates suggest >$50 million/year in spend), the economics usually don’t work out. Small to mid-sized advertisers would burn more on salaries and ops than they could possibly recoup in savings.

How Long Does It Take to Build Your Own Demand-Side Platform?

You can expect at least a year or two of development before a feature-complete DSP is ready. In practice, progress is slow and bugs are inevitable. One media consultant warns that the biggest hidden cost is

“miscalculating how much time and effort will be required.”

During that ramp-up period, competitors keep moving; in-house teams often struggle just to integrate basic things like ads.txt, header bidding, and verification tags. Moreover, the programmatic landscape is dominated by a few giants,

“the top 5 DSPs capture ~78% of all available impressions,”

so a small new DSP may see very little liquidity unless it can quickly match scale and publisher connections.

Who Do I Need to Build My Own DSP?

Running a DSP requires a deep team: you need RTB/machine-learning engineers, distributed systems developers, big-data specialists, UI developers, DevOps/cloud experts, plus media-buying operators and analysts.

Moreover, at some point, you’ll need a marketing team, a support team, and a QA team.

Such talent is scarce and expensive. Brand HR teams often struggle to fill “DSP engineer” or “programmatic manager” roles.

Even if built, the platform then requires constant upkeep for new ad formats, GDPR/CCPA compliance, ad space, fraud protection, and other ongoing tasks.

Many companies underestimate these challenges; historically, firms like Vodafone have given up on in-house DSP plans after encountering how much it costs and how many people are needed to be involved.

How to Build Your Own DSP?

So, you’re still here? Good, that means you either have enough resources or ambition, and you can’t build a DSP without either. Now let’s talk about how to actually do that.

Step # 1. Review Your Budgets and Set Realistic Goals

First of all, this is not a sprint – this is a marathon, quite a painful one, actually. If you want to finish it, then set realistic thresholds, document your mission/progress, and set KPIs.

Full-stack ownership is expensive and is usually justified only by massive media buying budgets. Our benchmark is based on what we’ve seen in the industry:

• Dev + infra baseline: $1.5M–$2.5M / year
• Core team overhead: ~$400k / year
• Combined baseline: $1.9M–$2.9M / year

These aren’t optional niceties; they’re baseline operating needs. If you don’t have this runway (or comparable ad spend to amortize the capex), you should strongly consider white-label or hybrid routes first.

Timeline goal: 4-8 weeks of planning is fine

Step # 2. Hire the Team

Someone has to build your DSP, don’t they? DSP is a product + operations business, so you’ll need engineers, ops, and programmatic specialists.

For starters, you’ll need:

• Head of Programmatic / Product (1) for product, roadmap, vendor & partner negotiations;
• Backend / RTB engineers (2–4) for bidder, ad server, pacing engine;
• Data engineers (1–2) for logging, pipelines, and OLAP setup;
• ML/Optimization engineer (1) for bid algorithms, lookalike scoring;
• Frontend/UI dev (1) for campaign management & reporting UI;
• DevOps / SRE (1–2) for deployment, monitoring, multi-region infrastructure;
• Ad Ops / Traders (1–3) for running campaigns, QA, optimizations;
• Legal/compliance or CPO consultant (0.5 FTE) for creating GDPR/CCPA & contracts;

Our personal advice (yeah, we’ve built a DSP before):

• Prioritize real time bidding protocol and distributed systems experience;
• Recruit flexible engineers who’ve worked with OpenRTB, Kafka/streaming, and low-latency systems;
• Budget for recruiting, competitive salaries, and retention bonuses;

Salaries vary by region; the $400k/year core team anchor assumes a lean, senior team in mixed geographies.

Step # 3. Design the Architecture

In 2025, DSPs are designed with latency, observability, and resilience. The core components you need to account for are (big brain info ahead):

• RTB Bidder (stateless, horizontally scalable): The real-time bidding decision logic should respond within approximately 50-150 ms for most marketplaces, with a p99 latency target below 200 ms to ensure competitiveness and meet exchange timeouts.
• Banker / Pacing Engine: Responsible for enforcing real-time budget controls, pacing spend smoothly across multiple exchanges and campaigns to avoid overspend or underspend.
• Ad Server / Creative Repository: Handles CDN-backed creative delivery, supports multiple ad formats, including VAST, VPAID alternatives, and native ads, with templates and dynamic creative optimization capabilities.
• Telemetry / Event Logging: Captures event-level data such as impressions, bids, wins, clicks, and viewability. This data is ingested into high-throughput message queues or streaming platforms (e.g., Kafka), then stored into OLAP systems (e.g., ClickHouse, BigQuery, Druid, or equivalent) to enable near real-time analytics and reporting.
• UI / API Layer: Provides interfaces for campaign setup, reporting dashboards, and rule engines, enabling marketing teams to configure and monitor DSP behavior.
• Storage Systems: Utilize high-performance key-value stores for fast access to relevant user segments and caching, alongside time-series or OLAP databases for analytical queries related to reports and metrics.
• Fraud Detection / Verification (Optional): A critical module that identifies and filters out invalid traffic, click fraud, and suspicious activity in real time or near real time to protect campaign budgets and maintain data quality. There are many methods to achieve that. In most cases, businesses integrate with third-party fraud prevention services or develop in-house anomaly detection algorithms.
• Optimization Engine / ML Models (Optional): Continuously analyzes historical and real-time data to adjust bidding strategies, targeting criteria, and budget allocation.

Step # 4. Integrate Supply

Unfortunately, connections to supply are not plug-and-play; you have to engineer everything by yourself.

Must-do integrations include:

• Implement OpenRTB adapters and custom exchange endpoints;
• Exchange contracts & tech certifications: Google AdX, PubMatic, OpenX, Amazon, BidSwitch, major SSPs;
• Implement ads.txt / sellers.json checks and supply chain verification.
• Connect verification and anti-fraud vendors (DV, IAS, Moat, or equivalents) for viewability/fraud checks.
• CMP integration and consent propagation for TCF/GDPR/CCPA.

Step # 5. Build the Minimum Viable Product (pilot, not perfect)

Don’t aim for a full feature set at launch. Ship an MVP that proves the core value: reliable ad buying with measurable ROI.

MVP scope should include:

• Core RTB bidder with basic targeting rules
• Campaign UI for line items, budgets, and creatives
• Banker/pacing engine to control spend
• Basic reporting (impressions, clicks, spend, CPM, CTR)
• One or two key exchange integrations (focus on high-liquidity partners)
• Consent handling and minimum fraud checks

How much time do you have?

The pilot version should take you from three to six months. That’ll cover things like a single channel (display or CTV/mobile), limited exchanges, and several traders.

For scale, 6 to 12 months is preferable. Add more exchanges, advanced bidding logic (ML-driven), richer reporting, and creative templates.

Step # 6. Testing and Optimization

Validate campaign performance, compliance, and supply chain integrity before scaling.

Pay close attention to:

• Load testing: simulate tens of thousands of requests per second, scaling to expected production volume. Don’t forget to measure p99 latency.
• Accuracy tests: verify bid logic, winner selection, and reporting align with actual auction outcomes;
• Fraud & brand safety: integrate verification tools, maintain blocklists, run post-buy audits;
• Privacy & compliance: integrate Consent Management Platform (CMP), handle consent storage, enforce data retention policies, and conduct Data Protection Impact Assessments (DPIA) where required;

Step # 7. Run!

It’s finally time to operate, iterate, and optimize. You’d think this is the end, but this is only when the fun begins.

Expand to additional channels, decide on your unique business model, scale your traffic offerings, and pay attention to latency, win rates, CPM efficiency, and reporting freshness, allowing advertisers to scale.

Also, don’t forget to check what the competition is doing. It’s always useful to keep your hand on the ad tech’s pulse.

White-Labeling: An Alternative to Building Your Own DSP

Okay, as you can see, building your own DSP is time-consuming and expensive. Obviously, not everyone can afford that. If you don’t have a year and several millions lying around (at least), then building your own demand-side platform is currently out of your reach.

That’s when you either outsource, buy a DSP, or white-label one.

If you’ve come so far reading this article, outsourcing is hardly the choice for you. The quality of media buying is not guaranteed, and the transparency is nonexistent.

Buying a self-serve DSP seems like a great alternative, but its primary target audience is ad tech beginners. Moreover, a single platform won't be enough, as self-serve DSPs typically come with a limited number of SSPs pre-installed.

On top of that, most modern DSPs already come with white-labeling as an option, so why not choose customization and freedom from the start?

Why White-Label Instead of Building?

A white-label DSP is essentially a DSP product that you lease and brand as your own. It offers most of the advantages of an in-house solution, but eliminates the need to build core technology.

In practice, a white-label DSP is a fully developed, customizable platform that you purchase without an external logo; you simply rebrand and configure it. This means you skip the multi-year development cycle: many white-label DSPs can be deployed “in days or weeks” rather than years of coding. All the basic DSP capabilities (precise targeting, bidding, reporting, integrations) come pre-built.

Essentially, you eliminate years of writing code to build a DSP with about 2-3 weeks to adapt. Moreover, you avoid the tech risks, all the hassle that comes with support/maintenance/compliance that comes with building a DSP.

What are the drawbacks? There are surprisingly few. You still pay for the service + % of the ad spend. Also, not all white-label DSPs support custom development, should you want to expand the feature list. Epom DSP does, however.

Should You Buy or Build a Custom DSP?

Let’s sum up all of the methods in an easy-to-use table: