Top 11 DataXu Alternatives for Programmatic Advertising in 2026

DataXu no longer exists as a standalone platform. In 2019, Roku acquired DataXu and merged it into what's now called Roku OneView — a platform focused primarily on Roku's own streaming inventory. For advertisers who relied on DataXu's cross-channel DSP capabilities, this shift created a gap. Teams running campaigns across Google, Meta, LinkedIn, programmatic display, and CTV need a platform that consolidates reporting, automates attribution, and doesn't lock them into a single publisher ecosystem.

This article reviews 11 DataXu alternatives built for programmatic advertising, omnichannel campaigns, and marketing analytics. You'll see what each platform does well, where it falls short, and how to choose the right stack for your team. We've included DSPs, marketing data platforms, and analytics tools — because real attribution requires both ad delivery and data infrastructure.

Key Takeaways

✓ DataXu was acquired by Roku in 2019 and no longer operates as an independent cross-channel DSP; teams need alternatives that support programmatic buying across multiple publishers.

✓ Most DSPs excel at ad delivery but lack the data layer needed for unified reporting — you'll often need a separate marketing data platform to connect campaigns to revenue.

✓ Self-serve DSPs like Google DV360 and The Trade Desk offer transparency and control, but require in-house expertise to manage bidding, creative, and attribution logic.

✓ Managed-service platforms like StackAdapt and Simpli.fi handle campaign execution for you, but limit access to raw performance data and customization.

✓ Marketing data platforms like Improvado don't replace your DSP — they unify reporting across all paid channels, automate attribution modeling, and eliminate the manual work of stitching together exports.

✓ The best setup for most teams is a DSP for ad buying plus a marketing data platform for measurement — trying to force a DSP to do both creates reporting gaps and slows decision-making.

What Is DataXu and Why Teams Are Looking for Alternatives

DataXu launched in 2007 as one of the early demand-side platforms built for programmatic advertising. It gave media buyers a unified interface to bid on display, video, and mobile inventory across multiple ad exchanges. The platform's strength was its cross-channel campaign orchestration — you could run a coordinated strategy across publishers without logging into separate DSPs or relying on managed services.

After Roku acquired DataXu, the platform pivoted toward Roku's owned-and-operated streaming inventory. Roku OneView still offers programmatic capabilities, but it's no longer positioned as a vendor-neutral DSP. For advertisers running campaigns beyond Roku's ecosystem — especially those who need detailed reporting across Google Ads, Meta, LinkedIn, TikTok, and programmatic display — the acquisition created a workflow gap. Teams now need alternatives that deliver both cross-channel ad buying and unified analytics without forcing them into a single publisher's walled garden.

How to Choose a DataXu Alternative: Evaluation Framework

Not every platform markets itself as a "DataXu replacement," but the underlying buyer need is consistent: run omnichannel campaigns, measure performance in one place, and avoid spending hours reconciling platform exports. Here's what to evaluate:

Ad inventory access. Does the platform give you bidding access to the ad exchanges and publishers your audience uses? Self-serve DSPs like DV360 and The Trade Desk connect to most major exchanges. Managed platforms like StackAdapt curate inventory for you, which speeds up campaign launch but limits transparency.

Reporting and attribution infrastructure. Most DSPs show in-platform metrics (impressions, clicks, conversions), but they don't connect ad spend to downstream revenue, pipeline, or customer lifetime value. If you need attribution beyond last-click or want to tie campaigns to Salesforce opportunities, you'll need a separate data layer — either a marketing data platform or a custom warehouse pipeline.

Self-serve vs. managed service. Self-serve platforms give you full control over bidding logic, creative, and audience targeting — but you need the team to manage it. Managed platforms handle execution for you and offer a dedicated rep, but they limit access to raw data and charge higher fees.

Data export and API access. If you're building custom dashboards or feeding campaign data into a BI tool, check whether the platform offers bulk exports, a real-time API, or scheduled reporting. Some DSPs (especially managed ones) only provide PDFs or locked-down UI dashboards.

Integration with your existing stack. Does the platform connect to your CRM, analytics warehouse, or BI tool without requiring custom engineering? Marketing data platforms like Improvado, Funnel, and Supermetrics specialize in this — they extract data from DSPs and other ad platforms, normalize it, and push it to your warehouse or dashboard tool.

Google Display & Video 360: Enterprise DSP with Full Google Ecosystem Integration

Google Display & Video 360 (DV360) is Google's enterprise demand-side platform. It gives advertisers programmatic access to display, video, audio, and native inventory across Google Ad Manager, YouTube, and third-party exchanges. DV360 is built for large media buyers who need granular control over bidding, frequency capping, and audience targeting. It integrates directly with Google Analytics 4, Campaign Manager 360, and Search Ads 360 — making it the default choice for teams already operating inside Google Marketing Platform.

Cross-Channel Campaign Management and Unified Frequency Capping

DV360's core strength is its ability to manage display, video, and audio campaigns from a single interface. You can set frequency caps that apply across YouTube, programmatic display, and Google's partner inventory — preventing the same user from seeing your ad eight times in one hour across different placements. The platform also supports sequential messaging, so you can show different creative to users based on where they are in the funnel.

The reporting layer connects to Google Analytics 4, which means you can measure conversions that happen on your website or app after someone clicks a DV360 ad. However, DV360 doesn't natively track conversions that happen in Salesforce, HubSpot, or your offline CRM. If you need to measure pipeline or revenue attribution, you'll need to build a custom integration or use a marketing data platform to join DV360 data with CRM data in a warehouse.

Steep Learning Curve and Limited Support for Small Teams

DV360 is not a self-service platform in the way Meta Ads Manager or LinkedIn Campaign Manager are. It requires a Google Marketing Platform account, a minimum spend commitment (typically $50,000+ per month), and either an in-house programmatic team or an agency partner certified by Google. The interface is built for power users — there's no campaign setup wizard, and you're expected to understand concepts like deal IDs, private marketplaces, and first-price auctions.

Google offers training resources and certification programs, but onboarding takes time. Small teams or those new to programmatic often find DV360 overwhelming compared to simpler platforms like StackAdapt or Simpli.fi, which offer managed services and faster setup.

The Trade Desk: Independent DSP with Transparency and Custom Deal Access

The Trade Desk is the largest independent DSP, meaning it's not owned by a publisher or media company. This gives advertisers access to inventory across nearly every major ad exchange — including Google Ad Manager, Amazon Publisher Services, Xandr, and hundreds of smaller SSPs. The platform is known for its transparency: you can see exactly where your ads ran, what you paid, and which supply paths delivered the best performance.

Kokai Platform and AI-Powered Bidding

The Trade Desk's Kokai operating system is its core bidding engine. It evaluates billions of ad impressions per second and uses machine learning to predict which inventory is most likely to drive conversions. You can customize bidding strategies based on your KPIs — whether that's video completion rate, site visits, app installs, or CRM-defined conversions.

The platform also supports custom deals and private marketplaces. If you have a direct relationship with a publisher or want guaranteed inventory during a high-demand period (like Black Friday), you can negotiate a deal ID and traffic it through The Trade Desk. This level of control is rare among DSPs — most managed platforms handle deal negotiation internally and don't expose the mechanics to advertisers.

Requires Programmatic Expertise and Ongoing Optimization

The Trade Desk is a self-serve platform, but it's not designed for beginners. You need someone on your team who understands programmatic buying — how to set floor prices, evaluate supply path optimization, manage data fees, and interpret bid landscape reports. The platform doesn't automate campaign setup the way Google's Performance Max or Meta's Advantage+ campaigns do. You're expected to define targeting, creative rotation, and conversion tracking logic yourself.

The Trade Desk offers training and certification, but most successful users are either experienced media buyers or work with an agency partner. If your team is new to programmatic, you'll likely need external support to get campaigns running efficiently.

StackAdapt: Managed Programmatic Platform with Built-In Creative Tools

StackAdapt is a managed DSP focused on native, display, video, and CTV advertising. It's positioned as a middle ground between fully self-serve platforms like The Trade Desk and traditional managed services where you hand off everything to an agency. StackAdapt provides the ad-buying infrastructure, a dedicated account manager, and built-in creative tools — but you still control campaign strategy, targeting, and budget allocation.

Native Advertising and Contextual Targeting

StackAdapt specializes in native ads — the sponsored content blocks you see on news sites, blogs, and content recommendation engines like Outbrain or Taboola. Native ads blend into the surrounding content, which often drives higher engagement than banner ads. StackAdapt's creative studio lets you build native units directly in the platform without needing a separate design tool.

The platform also offers contextual targeting powered by machine learning. Instead of relying solely on third-party audience cookies, StackAdapt analyzes the content of the page where your ad will appear — matching your creative to articles, videos, or forums that align with your product. This approach has become more important as browser privacy features and GDPR enforcement reduce the availability of cookie-based targeting.

Limited Data Export and Reporting Flexibility

StackAdapt provides in-platform dashboards and scheduled reports, but it doesn't offer the same level of raw data access as The Trade Desk or DV360. If you want to pull campaign performance into your own BI tool or join it with Salesforce data in a warehouse, you'll need to export CSVs manually or use a third-party connector. StackAdapt does offer an API, but it's primarily designed for internal use and requires approval for external access.

For teams that want to build custom attribution models or analyze performance across dozens of campaigns at once, this limitation creates extra work. You're dependent on StackAdapt's reporting interface, which is well-designed but not as flexible as querying raw data in SQL or building your own dashboards in Looker or Tableau.

Simpli.fi: Localized Programmatic Advertising for Multi-Location Brands

Simpli.fi is a managed DSP built for advertisers who need localized programmatic campaigns — franchises, retail chains, healthcare systems, and real estate companies. The platform specializes in geo-targeting, addressable advertising, and CTV campaigns that reach specific DMAs or zip codes. Simpli.fi handles campaign setup, optimization, and reporting, so you don't need an in-house programmatic team.

Addressable Geo-Fencing and Household-Level Targeting

Simpli.fi's standout feature is its geo-targeting precision. You can define custom polygons around physical locations — a specific store, a competitor's location, or an event venue — and serve ads to people who enter or have recently visited that area. The platform also supports addressable targeting, where you upload a list of physical addresses (from your CRM or a third-party data provider) and Simpli.fi matches them to households for CTV or display campaigns.

This is particularly useful for multi-location brands that want to run different creative or offers based on geography. For example, a retail chain could promote a store opening in Dallas while running a clearance sale in Boston — all managed from the same campaign interface.

Fully Managed Service with Limited Transparency

Simpli.fi is a white-glove service, which means you work with a dedicated team that sets up campaigns, manages bidding, and provides reporting. This makes it accessible for teams without programmatic expertise, but it also limits control. You can't log in and adjust bids yourself, view supply path data, or export raw impression logs. If you want to change targeting mid-campaign, you submit a request to your account manager.

The reporting is also less granular than self-serve platforms. You'll receive scheduled dashboards and PDFs, but you won't have access to an API or real-time data export. For teams that need to integrate campaign data into a warehouse or build custom attribution models, this creates a dependency on Simpli.fi's reporting cadence.

Amazon DSP: Programmatic Access to Amazon's First-Party Shopping Data

Amazon DSP is Amazon's demand-side platform, offering programmatic access to display, video, and audio inventory across Amazon-owned properties (like IMDb and Twitch) and third-party publishers. The platform's unique advantage is its first-party shopping data — you can target audiences based on what they've browsed, added to cart, or purchased on Amazon, even if you're not an Amazon seller.

First-Party Amazon Audiences and Product Retargeting

Amazon DSP lets you build audiences based on Amazon shopping behavior. For example, you can target people who viewed a competitor's product but didn't buy, or people who purchased a complementary product in the last 30 days. This is especially powerful for e-commerce brands, CPG companies, and anyone selling products on Amazon — you can use programmatic ads to influence purchase decisions before someone ever lands on your product page.

The platform also supports video ads on Amazon properties, including Fire TV and IMDb. If you're running a product launch or seasonal campaign, you can coordinate display retargeting with video awareness ads across Amazon's ecosystem.

High Minimum Spend and Complex Onboarding

Amazon DSP requires a minimum spend commitment — typically $35,000 for self-service accounts or $50,000+ for managed service. If you're a small advertiser or new to programmatic, this creates a barrier. The platform also has a steep learning curve: the interface is dense, reporting is siloed from other Amazon Advertising tools (like Sponsored Products), and there's limited support documentation compared to Google or Meta.

Amazon DSP reporting also doesn't connect natively to non-Amazon analytics tools. If you want to measure how Amazon DSP campaigns impact website conversions tracked in Google Analytics or Salesforce, you'll need to build a custom integration or use a marketing data platform to join the data.

Roku OneView: CTV Advertising with First-Party Streaming Data

Roku OneView is what became of DataXu after Roku acquired the company. It's now a CTV-first advertising platform focused on Roku's 80 million+ active streaming households. Roku OneView gives advertisers access to video inventory on The Roku Channel, Roku's home screen placements, and third-party streaming apps available on Roku devices. The platform uses Roku's first-party viewing data to target audiences based on what they watch, how long they watch, and which apps they use.

CTV-Specific Measurement and Household Targeting

Roku OneView specializes in connected TV advertising, which means it's built for full-screen video ads shown on TVs rather than mobile or desktop. The platform tracks metrics like video completion rate, household reach, and frequency — all at the device level. You can target households based on Roku's first-party data (viewing behavior, app usage) or upload your own CRM list for addressable campaigns.

Roku also offers measurement tools like brand lift studies and attribution reporting that connects CTV ad exposure to website visits or app installs. However, this attribution is limited to Roku's ecosystem — you won't get visibility into how Roku ads perform alongside your Google, Meta, or TikTok campaigns unless you manually combine the data.

Narrow Inventory Focus and No Cross-Channel Orchestration

Roku OneView is not a cross-channel DSP. It only sells Roku inventory — you can't use it to buy display ads on Google, native ads on Outbrain, or video on YouTube. If you're running an omnichannel campaign, you'll need to manage Roku separately from your other channels and manually reconcile performance data.

This is a major shift from DataXu's original value proposition, which was cross-channel campaign orchestration. Teams that relied on DataXu for unified programmatic buying now need a separate DSP (like DV360 or The Trade Desk) plus a marketing data platform to unify reporting across all channels.

Adobe Advertising Cloud: Integrated DSP for Adobe Experience Cloud Users

Adobe Advertising Cloud is Adobe's demand-side platform, built for enterprise advertisers already using Adobe Experience Cloud (Analytics, Target, Audience Manager). It offers programmatic buying across display, video, native, and CTV inventory, with deep integration into Adobe's customer data and analytics stack. The platform is designed for large brands that want to connect ad delivery to personalization, testing, and attribution — all within Adobe's ecosystem.

Deep Adobe Ecosystem Integration and Cross-Channel Attribution

Adobe Advertising Cloud's primary advantage is its connection to Adobe Analytics and Adobe Audience Manager. You can build audiences in Audience Manager (based on website behavior, CRM data, or third-party segments), activate them in Advertising Cloud, and measure performance in Adobe Analytics — all without exporting data or using third-party connectors. The platform also supports cross-channel attribution modeling, so you can see how display, video, and search campaigns influence conversions across touchpoints.

For teams that already rely on Adobe for analytics and personalization, this integration eliminates data silos and speeds up campaign execution. You're working in a unified environment instead of stitching together exports from five different tools.

High Cost and Long Implementation Timeline

Adobe Advertising Cloud is an enterprise product with enterprise pricing. Licensing typically starts at six figures annually, and implementation can take months — especially if you're integrating it with Adobe Analytics, Audience Manager, and Target. Adobe expects you to have a dedicated team (or agency partner) managing campaigns, optimization, and reporting. Small teams or mid-market advertisers often find the platform too complex and expensive compared to alternatives like StackAdapt or Simpli.fi.

The reporting interface is also built for Adobe power users. If your team isn't already familiar with Adobe Analytics workspace or calculated metrics, the learning curve is steep. Adobe offers training and certification, but onboarding takes time and requires ongoing investment in team education.

MediaMath: Open-Architecture DSP with Customizable Algorithms

MediaMath is an independent DSP focused on transparency and customization. It gives advertisers access to a wide range of inventory sources (display, video, native, CTV, audio) and allows them to build custom bidding algorithms using MediaMath's TerminalOne platform. The platform is popular among agencies and large advertisers who want control over supply path optimization, deal negotiation, and algorithmic bidding logic.

Custom Algorithmic Bidding and Supply Path Transparency

MediaMath lets you define your own bidding strategies using a combination of pre-built algorithms and custom logic. You can optimize for conversions, viewability, brand safety, or any metric your team cares about — and you can adjust the algorithm mid-campaign based on performance. This level of control is rare among DSPs, most of which use black-box machine learning models that you can't customize.

The platform also provides supply path transparency, showing you exactly which SSPs, exchanges, and publishers delivered each impression. You can evaluate supply path performance and cut out intermediaries that add fees without improving results. This is especially valuable for large advertisers concerned about ad fraud, domain spoofing, or wasted spend.

Complex Setup and Requires Programmatic Expertise

MediaMath is built for experienced programmatic buyers. The interface assumes you understand concepts like bid shading, header bidding, and dynamic creative optimization. If you're new to programmatic or don't have a team that can manage algorithmic bidding, MediaMath will feel overwhelming. The platform offers training and support, but it's not a managed service — you're expected to handle campaign setup, optimization, and troubleshooting yourself.

Reporting is also more technical than most DSPs. MediaMath provides detailed logs and API access, but you'll need to export data and analyze it in your own BI tool or warehouse. The platform doesn't offer pre-built dashboards or simplified reporting views the way StackAdapt or Simpli.fi do.

Funnel: Marketing Data Platform for Automated Reporting Across Ad Platforms

Funnel is a marketing data platform that collects, transforms, and centralizes data from ad platforms, analytics tools, and CRMs. It doesn't replace your DSP — instead, it solves the reporting problem that most DSPs create. Funnel connects to 500+ data sources (including Google Ads, Meta, LinkedIn, DV360, The Trade Desk, and dozens of programmatic platforms), normalizes the data, and pushes it to your BI tool or data warehouse. This eliminates the manual work of exporting CSVs, reconciling metrics, and building custom API pipelines.

Pre-Built Connectors and Automated Data Collection

Funnel's core feature is its library of pre-built connectors. You authenticate each ad platform once, and Funnel automatically pulls campaign performance data on a daily (or hourly) schedule. The platform handles API pagination, rate limits, and schema changes — so you're not building and maintaining custom scripts every time Meta or Google updates their API.

Funnel also normalizes metrics across platforms. For example, Meta calls it "Amount Spent," Google calls it "Cost," and LinkedIn calls it "Total Budget" — Funnel maps these to a single "Spend" field so you can compare performance without manual cleanup. This is especially useful if you're running campaigns across five or ten platforms and need a unified view of ROAS, CPA, or conversion volume.

Limited Data Transformation and No Built-In Attribution Modeling

Funnel is a data pipeline, not an analytics platform. It collects and centralizes data, but it doesn't perform advanced transformations or build attribution models for you. If you want to calculate multi-touch attribution, join ad spend to Salesforce pipeline, or create custom marketing mix models, you'll need to do that work in your BI tool or warehouse after Funnel delivers the data.

Funnel also charges based on data volume and the number of connectors you use. For small teams running campaigns on three or four platforms, the pricing is manageable. But if you're an agency managing 50 clients or an enterprise with hundreds of campaigns, costs can scale quickly. Funnel offers volume discounts, but it's not the cheapest option for high-scale use cases.

Supermetrics: Budget-Friendly Marketing Data Connector for Small Teams

Supermetrics is a marketing data connector that pulls data from ad platforms, analytics tools, and social media into Google Sheets, Excel, Looker Studio, Power BI, or your data warehouse. It's similar to Funnel but optimized for small teams and individual marketers who need a low-cost way to automate reporting. Supermetrics is popular among agencies, freelancers, and in-house teams that don't have engineering resources but still want to centralize campaign data.

Google Sheets and Looker Studio Integration

Supermetrics' most popular use case is pulling campaign data into Google Sheets. You install the Supermetrics add-on, select a data source (like Google Ads or Meta Ads), and choose the metrics and dimensions you want. Supermetrics fetches the data and loads it into your spreadsheet on a schedule you define. This makes it easy to build custom reports, combine data from multiple platforms, and share dashboards with stakeholders who prefer spreadsheets over BI tools.

Supermetrics also integrates with Looker Studio (formerly Google Data Studio), letting you build visual dashboards that refresh automatically. You can create charts, tables, and scorecards that pull live data from Meta, Google Ads, LinkedIn, and other platforms — without writing SQL or setting up a warehouse.

Doesn't Scale for Enterprise Use Cases

Supermetrics works well for small teams managing a handful of campaigns, but it struggles at scale. The platform doesn't offer advanced data transformation, centralized data governance, or the ability to join ad data with CRM or warehouse data in a structured way. If you're managing hundreds of campaigns or need to build multi-touch attribution models, you'll outgrow Supermetrics quickly.

The pricing model is also per-destination: if you want to send data to Google Sheets and Looker Studio and your warehouse, you're paying for three separate subscriptions. For agencies managing multiple clients or enterprises with complex data workflows, this becomes expensive and difficult to manage.

Improvado: Enterprise Marketing Data Platform with Pre-Built Attribution Models

Improvado is a marketing data platform built for mid-market and enterprise teams that need to centralize data from hundreds of sources, automate attribution modeling, and enforce data governance across campaigns. Unlike Funnel or Supermetrics, Improvado isn't just a data pipeline — it includes pre-built transformation logic, marketing-specific data models, and tools for validating campaign data before it's reported.

500+ Pre-Built Connectors and Marketing Cloud Data Model

Improvado connects to over 500 marketing and sales platforms — including every major DSP (DV360, The Trade Desk, Amazon DSP, StackAdapt), ad network (Google Ads, Meta, LinkedIn, TikTok), CRM (Salesforce, HubSpot), and analytics tool (Google Analytics, Adobe Analytics). Each connector is maintained by Improvado's engineering team, so when a platform updates its API or changes its schema, Improvado handles the migration and preserves your historical data for up to two years.

Improvado also provides a Marketing Cloud Data Model (MCDM) — a pre-built schema designed specifically for marketing analytics. Instead of dumping raw API responses into your warehouse, Improvado transforms the data into a consistent structure with standardized metrics (Spend, Impressions, Clicks, Conversions), campaign hierarchies, and UTM fields. This eliminates weeks of data modeling work and ensures your dashboards are built on clean, reliable data.

Marketing Data Governance and Pre-Launch Validation

Improvado includes a data governance layer with over 250 pre-built validation rules. These rules check for common errors — missing UTM parameters, duplicate campaign names, budget overruns, naming convention violations — before data flows into your warehouse or BI tool. If a campaign launches without proper tracking, Improvado flags it immediately so your team can fix it before reporting breaks.

This governance layer is especially valuable for agencies and enterprises managing hundreds of campaigns across multiple teams. Without automated validation, errors compound — you don't discover a tracking problem until weeks later when you're reconciling monthly reports. Improvado catches those errors at the source, so your reporting stays accurate in real time.

Not a DSP — Requires Separate Ad-Buying Platform

Improvado doesn't buy ads or manage campaigns. It's a data platform, not a DSP. If you need to launch programmatic campaigns, you'll still use DV360, The Trade Desk, or another DSP — Improvado's job is to collect the performance data from those platforms and unify it with data from Google Ads, Meta, Salesforce, and your other tools. For teams that only need a simple dashboard and don't run campaigns across multiple channels, Improvado may be overkill compared to a lighter tool like Supermetrics or Looker Studio.

DataXu Alternatives Comparison Table

How to Get Started with DataXu Alternatives

Choosing the right DataXu replacement depends on whether you need ad-buying capabilities, data infrastructure, or both. Here's how to approach the decision:

Step 1: Define what DataXu did for you. If you primarily used DataXu to buy programmatic ads across multiple exchanges, you need a DSP. If you used it to consolidate reporting across channels, you need a marketing data platform. Most teams need both — a DSP for ad delivery and a data platform for measurement.

Step 2: Decide between self-serve and managed. Self-serve DSPs (DV360, The Trade Desk, MediaMath) give you full control but require programmatic expertise. Managed platforms (StackAdapt, Simpli.fi, Roku OneView) handle execution for you but limit transparency and data access. If you don't have a programmatic team in-house, start with a managed platform or hire an agency partner.

Step 3: Evaluate your reporting requirements. If you're running campaigns on more than three platforms and need unified attribution, you'll need a marketing data platform. Tools like Improvado, Funnel, and Supermetrics eliminate the manual work of exporting data and building dashboards. Improvado is the best choice for enterprises that need governance, advanced transformation, and pre-built attribution models. Funnel works for mid-market teams that want automated data collection without heavy customization. Supermetrics is ideal for small teams on a budget who can manage reporting in Google Sheets or Looker Studio.

Step 4: Test with a pilot campaign. Most DSPs and data platforms offer trial periods or pilot programs. Start with a small budget and a single campaign to evaluate performance, reporting quality, and support responsiveness. Compare metrics like setup time, data accuracy, and how long it takes to get answers from the platform's support team.

Step 5: Build your integration stack. If you're using a DSP plus a marketing data platform, make sure they integrate cleanly. Check whether the data platform has a pre-built connector for your DSP, whether it supports the metrics you care about, and whether it can join ad data with your CRM or analytics tool. Improvado's 500+ connectors cover nearly every DSP and ad platform, which eliminates the need for custom API work.

Conclusion

DataXu's acquisition by Roku and shift toward CTV-only inventory left a gap for advertisers who need cross-channel programmatic buying and unified reporting. The platforms reviewed in this article offer different solutions — some focus on ad delivery (DV360, The Trade Desk, StackAdapt), others focus on data infrastructure (Improvado, Funnel, Supermetrics), and a few try to do both with limitations.

For most marketing teams, the best setup is a DSP for ad buying plus a marketing data platform for measurement. This separation lets you choose the DSP that fits your inventory needs (Google, independent, CTV-focused) and the data platform that fits your reporting complexity (enterprise governance, budget-friendly automation, or simple Sheets integration). Trying to force a DSP to handle attribution, data quality, and cross-platform reporting creates gaps — you end up with siloed dashboards, manual reconciliation, and campaigns that can't be compared accurately.

If you're running campaigns across multiple DSPs, ad networks, and CRMs — and you need attribution models that go beyond last-click — Improvado provides the infrastructure to unify that data, enforce governance, and deliver accurate reporting without requiring engineering resources. Teams using Improvado eliminate the manual export-and-merge workflow, reduce reporting errors by over 80%, and free up analysts to focus on optimization instead of data cleanup.

Frequently Asked Questions

Does DataXu still exist as a platform?

No. DataXu was acquired by Roku in 2019 and merged into Roku's advertising platform, now called Roku OneView. The original DataXu cross-channel DSP no longer operates as a standalone product. Roku OneView focuses primarily on CTV advertising within Roku's ecosystem, not the multi-platform programmatic buying that DataXu originally offered. Teams that relied on DataXu for cross-channel campaigns now need an alternative DSP or a combination of DSP plus marketing data platform.

What is the best DataXu alternative for cross-channel programmatic advertising?

The best alternative depends on your team's needs. Google DV360 and The Trade Desk are the strongest self-serve DSPs for cross-channel programmatic, offering access to most major ad exchanges and transparent reporting. StackAdapt and Simpli.fi are better choices if you want managed services and don't have in-house programmatic expertise. However, most DSPs don't solve the reporting and attribution problem — for that, you need a marketing data platform like Improvado to unify data across all your ad platforms and connect campaigns to revenue.

Do I need a DSP or a marketing data platform?

You likely need both. A DSP (like DV360, The Trade Desk, or StackAdapt) is what you use to buy ads — it connects to ad exchanges and manages bidding, targeting, and creative delivery. A marketing data platform (like Improvado, Funnel, or Supermetrics) is what you use to collect performance data from your DSP and other ad platforms, normalize it, and push it into your BI tool or warehouse for unified reporting. Most DSPs provide in-platform dashboards, but they don't connect ad spend to downstream revenue, multi-touch attribution, or CRM data — that's what a marketing data platform does.

Should I use The Trade Desk or Google DV360?

Both are strong self-serve DSPs, but they serve different needs. DV360 is the better choice if you're already using Google Marketing Platform (Google Analytics, Campaign Manager, Search Ads 360) and want tight integration across Google's ecosystem. The Trade Desk is better if you want an independent DSP with transparent supply path reporting, custom deal access, and no publisher conflicts of interest. Both require programmatic expertise — if you don't have a team that can manage bidding and optimization, consider a managed platform like StackAdapt instead.

Is Amazon DSP worth the high minimum spend?

Amazon DSP is worth it if you're an e-commerce brand, CPG company, or anyone selling products on Amazon and you want to target audiences based on Amazon shopping behavior. The platform's first-party data (what people browse, add to cart, and purchase on Amazon) is unique and highly effective for product retargeting and competitive conquest campaigns. However, the $35,000+ monthly minimum spend makes it inaccessible for small advertisers. If you don't meet the minimum or don't sell on Amazon, other DSPs like The Trade Desk or StackAdapt will deliver better ROI.

What's the difference between Funnel and Improvado?

Both are marketing data platforms that automate data collection from ad platforms, but they serve different scales and use cases. Funnel is designed for mid-market teams that need automated data pipelines without heavy customization — it's easy to set up, supports 500+ connectors, and integrates with most BI tools. Improvado is built for enterprises and agencies that need advanced transformation logic, pre-built attribution models, data governance, and dedicated support for custom connectors. Funnel is a data pipeline; Improvado is a data platform with governance, modeling, and validation built in. If you're managing hundreds of campaigns or need to enforce data quality rules, Improvado is the stronger choice.

Should I use a managed DSP or a self-serve DSP?

Use a managed DSP (StackAdapt, Simpli.fi, Roku OneView) if you don't have in-house programmatic expertise and you want a team to handle campaign setup, optimization, and reporting for you. Managed platforms are faster to launch and require less internal training, but they limit transparency and data access. Use a self-serve DSP (DV360, The Trade Desk, MediaMath) if you have experienced media buyers on your team and you want full control over bidding, targeting, and supply path optimization. Self-serve platforms offer more flexibility and transparency but require ongoing management and technical expertise.

How long does it take to set up a DataXu alternative?

Setup time varies by platform. Managed DSPs like StackAdapt or Simpli.fi can launch campaigns within a few days — you provide creative and targeting specs, and the platform's team handles the rest. Self-serve DSPs like DV360 or The Trade Desk require 2–4 weeks of onboarding, training, and campaign configuration, especially if your team is new to programmatic. Marketing data platforms like Improvado typically take 2–6 weeks to implement, depending on how many data sources you're connecting and whether you need custom transformations or attribution models. Most platforms offer pilot programs or trial periods so you can test before committing to a long-term contract.