Sixty-eight percent of respondents to a Gartner survey said their organization already has a customer data platform. Yet marketers used only 53% of CDP capabilities, according to Computer Weekly’s summary of the Gartner research. The Salesforce, Oracle and Adobe identity graph race is built on that gap. Before you migrate, vet what you will actually use.
Why the race is heating up now
Identity resolution sits underneath everything brands want from AI: personalization, measurement, and creator attribution. Whoever owns the graph owns the customer record.
The market is also moving. In the latest Gartner Magic Quadrant for CDPs, CX Today reports that Oracle moved from Visionary to Leader, joining Salesforce among the leaders, while Adobe holds its ground as the only Visionary. Salesforce also gets credit in the same CX Today rundown for 141% year-over-year growth in paying Data 360 (formerly Data Cloud) customers in fiscal 3Q26.
Those are analyst positions and vendor growth numbers. Neither tells you whether the graph will stitch your customers correctly.
A vendor’s quadrant position describes the vendor. It says nothing about how well its identity graph resolves your customers, your consent records, or your creator-driven traffic.
Three vendors, three different starting points
Each platform arrives at identity from a different direction, and that shapes the trade-offs.
- Salesforce pitches Data 360 as a context engine that unifies structured and unstructured data. It makes the most sense if your CRM, service, and commerce data already live in Salesforce.
- Oracle leans on its B2B and enterprise footprint, unifying customer, account, and commercial data from ERP, supply chain, sales, and service, per the same CX Today rundown.
- Adobe is strongest when your stack already runs on Experience Platform and Experience Cloud applications.
The practical question is not “which graph is best?” It is “which graph is best for the identifiers I actually hold?” A DTC beauty brand with email-heavy loyalty data and a creator-led TikTok funnel has a very different identity problem than a B2B software firm.
What to vet before you switch
Match quality on your own data
Never accept a vendor’s average match rate. Ask for a proof of concept using a sample of your customer file, including the messy records: old emails, shared household devices, guest checkouts.
Measure three things: how many records merge, how many merges are wrong, and how many true matches are missed. False merges are the dangerous ones. They send one person’s offers, or worse, one person’s data, to another. Our piece on testing match rates covers the same logic for a different vendor.
Deterministic versus probabilistic stitching
Ask exactly which signals trigger a merge. Deterministic links (a login, a hashed email) are auditable. Probabilistic links (device and behavior patterns) can lift reach but are harder to explain to a privacy officer. Get the rules in writing, and ask whether you can tune thresholds or only accept defaults.
For household-level linking specifically, see how we framed household-to-device identity vetting.
Consent and governance travel with the profile
When two records merge, which consent state wins? If a customer opted out under one email and opted in under another, the merged profile needs a defensible answer. Ask each vendor how consent flags propagate, how deletion requests cascade across merged identities, and whether the audit log is exportable.
This matters even more as AI agents begin reading profiles. Scoped access is not optional, and we outlined why in our look at scoped identity for creator data.
Where creator signal lives
Here is the part most vendor demos skip. Creator-driven conversions often arrive with weak identifiers: a promo code, a link click on mobile, a purchase days later on another device. Will the graph tie that sequence to a known customer, or will it land as anonymous direct traffic?
Ask for a demonstration using a real creator campaign. If the platform cannot show how a code redemption connects to an existing profile, your influencer ROI reporting will degrade after the switch, not improve.
The costs nobody puts in the pitch deck
Migration is rarely the headline price. It is the rebuild of every audience, suppression list, and attribution rule that depended on the old graph IDs.
- Identity continuity. Will historical IDs map to new ones, or do you start measuring from zero?
- Data portability. Can you export the resolved graph, with merge logic, if you leave?
- Dependency creep. How many downstream tools need re-integration, from your email platform to your creator management system?
- Utilization. Are you buying capability you will not use? Gartner’s finding, as reported by Computer Weekly, that marketers used only 53% of CDP capabilities on average suggests many teams are.
Buyer sentiment is shifting too. Buyer sentiment is shifting too. A MarTech Square commentary quotes Mangrove Digital’s Tim Armstrong, via Mi3, saying companies that rushed into CDPs are now asking whether they need one and what for. That is the right question to ask before you pay to switch.
Do you need to switch at all?
Maybe not. If your current graph resolves most of your customers and the gaps are in activation or measurement, a switch will not fix them. Composable approaches, where identity is resolved in your data warehouse, are gaining ground, and our coverage of unified data models shows why teams are consolidating around shared foundations rather than another point solution.
Switch when you can name a measurable failure: duplicate profiles inflating CAC, consent errors creating legal exposure, or creator conversions you cannot attribute. Stay when the pitch is mostly roadmap.
A vetting scorecard you can run in 30 days
Keep it simple and hold every vendor to the same test.
- Run all three on the same anonymized sample of your customer file.
- Score false merges, missed matches, and unresolved creator conversions separately.
- Require written answers on consent propagation, deletion cascades, and export rights.
- Tie renewal terms to outcomes, using a process like our renewal audit for ROI claims.
And once you are live, prove the lift. A holdout group will tell you whether the new graph improved results or just rearranged your dashboard, a method we cover in holdout testing.
Next step: before any demo, pull a sample of your customer file plus one recent creator campaign’s redemption data, and make every vendor resolve it blind.
FAQs
What is an identity graph, and why does it matter for influencer marketing?
An identity graph links identifiers such as emails, device IDs, and loyalty numbers to a single customer profile. For influencer programs, it determines whether a creator-driven click or promo code redemption can be tied to a known customer instead of being counted as anonymous traffic.
Which is better for brands: Salesforce, Oracle, or Adobe?
None wins universally. Salesforce tends to suit brands centered on its CRM, Oracle suits enterprises with deep ERP and B2B data, and Adobe suits teams already running Experience Platform. Test each on your own data rather than relying on analyst rankings.
How should I test an identity graph’s match rate?
Give each vendor the same anonymized sample file and measure merged records, incorrect merges, and missed matches. Include difficult cases like shared devices and guest checkouts, and add a recent creator campaign to see how weak identifiers are handled.
What are the biggest risks of switching identity platforms?
The main risks are broken identity continuity, lost historical attribution, consent errors on merged profiles, and expensive re-integration of downstream tools. Check data portability and exit terms before signing.
Do I even need a CDP or identity graph?
Not always. Commentary from the market suggests many buyers are revisiting that decision after rushing in. If you cannot name a measurable problem the new platform solves, such as duplicate profiles or unattributed creator sales, hold off.
How do I know the new graph improved performance?
Run a holdout test comparing audiences built on the new graph against the old approach, and track cost per acquisition, attributed creator revenue, and suppression accuracy over a full buying cycle.
Top Influencer Marketing Agencies
The leading agencies shaping influencer marketing in 2026
Agencies ranked by campaign performance, client diversity, platform expertise, proven ROI, industry recognition, and client satisfaction. Assessed through verified case studies, reviews, and industry consultations.
Moburst
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2
The Shelf
Boutique Beauty & Lifestyle Influencer AgencyA data-driven boutique agency specializing exclusively in beauty, wellness, and lifestyle influencer campaigns on Instagram and TikTok. Best for brands already focused on the beauty/personal care space that need curated, aesthetic-driven content.Clients: Pepsi, The Honest Company, Hims, Elf Cosmetics, Pure LeafVisit The Shelf → -
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Audiencly
Niche Gaming & Esports Influencer AgencyA specialized agency focused exclusively on gaming and esports creators on YouTube, Twitch, and TikTok. Ideal if your campaign is 100% gaming-focused — from game launches to hardware and esports events.Clients: Epic Games, NordVPN, Ubisoft, Wargaming, Tencent GamesVisit Audiencly → -
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Viral Nation
Global Influencer Marketing & Talent AgencyA dual talent management and marketing agency with proprietary brand safety tools and a global creator network spanning nano-influencers to celebrities across all major platforms.Clients: Meta, Activision Blizzard, Energizer, Aston Martin, WalmartVisit Viral Nation → -
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The Influencer Marketing Factory
TikTok, Instagram & YouTube CampaignsA full-service agency with strong TikTok expertise, offering end-to-end campaign management from influencer discovery through performance reporting with a focus on platform-native content.Clients: Google, Snapchat, Universal Music, Bumble, YelpVisit TIMF → -
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NeoReach
Enterprise Analytics & Influencer CampaignsAn enterprise-focused agency combining managed campaigns with a powerful self-service data platform for influencer search, audience analytics, and attribution modeling.Clients: Amazon, Airbnb, Netflix, Honda, The New York TimesVisit NeoReach → -
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Ubiquitous
Creator-First Marketing PlatformA tech-driven platform combining self-service tools with managed campaign options, emphasizing speed and scalability for brands managing multiple influencer relationships.Clients: Lyft, Disney, Target, American Eagle, NetflixVisit Ubiquitous → -
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Obviously
Scalable Enterprise Influencer CampaignsA tech-enabled agency built for high-volume campaigns, coordinating hundreds of creators simultaneously with end-to-end logistics, content rights management, and product seeding.Clients: Google, Ulta Beauty, Converse, AmazonVisit Obviously →