How telco signals improved audience alignment in Blis tests

The targeting question starts with data quality

Choosing a replacement for cookies starts with the data used to select audiences. In a Sapio Research survey published by Blis, 95% of respondents were significantly concerned about how long their current data strategies would remain viable. For marketers evaluating alternative signals, that concern makes the quality of audience inputs an immediate decision.

To examine those inputs, Blis combined a survey of 200 senior UK marketing decision-makers with separate audience-targeting campaign tests. The survey captures marketers’ concerns and expectations, while the tests measure what changed when telecommunications signals were added to an existing targeting setup. Blis supplies the telco-derived targeting approach being evaluated and benefits commercially from its adoption, so both components are part of one supplier-led research effort.

The decision matters as cookie-free traffic grows, third-party cookies decline and privacy rules tighten. These changes make alternative signals more important, but availability alone says little about their targeting value. Assessing that value means distinguishing audience affinity, how closely an audience’s interests and activities match a category, from commercial performance and reliability over time.

Marketers question the inputs that shape their audiences

The survey places accuracy ahead of signal loss among marketers’ reported targeting obstacles. Sapio Research found that 59% identified accuracy as their biggest audience-targeting obstacle, compared with 45% identifying cross-platform consistency and 39% identifying signal loss or user privacy challenges. For teams reviewing their data strategy, these responses make accuracy a central question when choosing which signals to retain or introduce.

Accuracy matters from the start because seed data, the starting information used to build an audience of similar people or expand an existing audience, shapes who gets selected. In the survey, 82% said the resulting audience depends on the quality of that starting information. If the seed gives an unreliable picture of the intended audience, expansion carries that uncertainty into campaign selection.

Respondents also linked input quality to campaign results: 78% said source data quality directly affects performance, while only 48% were confident that their existing audience inputs met their accuracy standards. These separate measures describe a group-level gap between the importance assigned to quality and confidence in current inputs. Blis interprets the gap as evidence that teams continue spending on digital campaigns while questioning the information behind their audience decisions.

That uncertainty becomes harder to manage when customer activity is split across separate systems. Almost seven in 10 respondents, or 69%, said single-channel and siloed data produced an insufficient, fragmented view of the customer journey. For these decision-makers, audience selection could draw on only parts of a customer’s activity, making the quality of the overall view harder to judge.

To address changing signal availability, advertisers are testing first-party data collected directly from customers and contextual targeting based on surrounding content. They are also testing clean rooms for controlled analysis of data from different parties and identity-based systems that connect activity to identifiers. Blis interprets the survey as suggesting that many marketers remain unconvinced that current substitutes fully address signal loss. For teams dependent on cookies, device identifiers or unreliable seed data, that concern gives them a reason to test additional inputs against their own targeting needs.

Telco signals add another view of audience activity

Blis proposes mobile-network data as one such input, drawing on signals including app usage and movement patterns. These give marketers another basis for deciding whom to target alongside their existing audience data. Blis presents network-derived signals as a potentially more durable option as established identifiers become less dependable, a proposition whose adoption would benefit its targeting business.

Survey respondents were receptive to that proposition. In the Sapio Research findings published by Blis, 82% agreed that telco data could become an essential signal for future omnichannel targeting, meaning targeting coordinated across advertising channels. Separately, 59% identified accuracy and quality as telco data’s main benefits. These responses describe expectations about its usefulness and future role.

Those expectations explain marketers’ interest, while the campaign tests examine a specific change to audience selection. Blis compared an existing targeting setup with the same setup enhanced by telco signals. The test therefore addresses a practical question for teams: whether another input improves the audience data they already use.

Adding telco signals improved affinity across all five tested categories

In that comparison, Blis reported statistically significant increases in category affinity across every category tested, with gains ranging from 38% to 155%. The exercise covered more than 3,500 respondents in selected UK geographies and used a 95% confidence threshold to assess statistical significance. Within this setup, Blis found that telco-enhanced audiences aligned more closely with their intended categories.

To assess alignment across different interests, Blis tested five audience segments through five verticals: Travel & Tourism, Health & Fitness, Food & Restaurants, Music & Movies, and Clothing & Fashion. Each vertical had a baseline audience and a telco-enhanced comparison. Blis built the baseline using location and spend signals together with Experian consumer segments and spend data, establishing a combination of inputs already used for targeting.

With that baseline in place, Blis used matched geographic areas to compare the two approaches. In the enhanced areas, it added telco-verified signals to the targeting criteria; control areas retained the baseline combination. Keeping the original inputs in both groups made it possible to test what the additional telco information contributed.

Participants then answered four questions about their relationship with the categories. The first asked about category interest, and the second asked which category generated their greatest engagement. The remaining questions asked about actions taken in the “last month” and actions expected in the “next three months.” Together, the responses brought general interest, reported past activity and expected future activity into the category-affinity assessment.

Blis compared the control and telco-enhanced responses within each vertical against its stated confidence threshold. It reported a statistically significant increase in every tested category, so the improvement extended across the full set of interests examined. Because the enhanced audiences retained the location, spend and Experian inputs, the result demonstrates what telco signals contributed when added to that combination.

For a team considering a similar addition, the comparison offers a practical test design: retain the existing inputs and assess what changes when the proposed signal is introduced. The test should reflect the advertiser’s audiences and operating conditions so that it informs an actual targeting decision. Its value then depends on what outcome the advertiser needs better category alignment to produce.

Affinity, commercial outcomes and network access need distinct measures

Category affinity helps assess audience selection, while sales, revenue, conversions and return on advertising spend measure commercial results. Participants’ reports of past actions and expected future actions add context to their interests; observed business outcomes measure what happens when a campaign runs. Reliability over time is a separate question, requiring repeated assessment across the periods in which an advertiser expects to use the signal.

Blis makes a broader commercial case for its approach. The company is part of T-Mobile Advertising Solutions, and Charlie Smith, Chief Revenue Officer at Blis, has a direct commercial interest in adoption of its offering. Smith describes signal loss as urgent for influential UK marketers and argues that traditional data sources are poorly suited to modern marketing needs.

Smith connects that argument to the systems that use audience data: “As modeling and automation play ever greater roles within digital, they can only ever be as good as their foundational seed data.” He argues that the quality of the starting information limits the decisions made from it. As teams give modeling and automation more responsibility, the inputs feeding those processes matter more.

Building on that argument, Smith describes the telco opportunity, delivered through an “omnichannel DSP” (a demand-side platform used to buy advertising across channels), as “simultaneously reliable, privacy-first, and highly actionable.” He also says: “This study demonstrates it can deliver exceptional precision and, crucially, outcomes,” extending his commercial proposition to precision and results. These are Smith’s claims for the offering; the comparative exercise measures category affinity within the tested setup.

Alongside those performance claims, Blis describes the scale of its network access. It says its UK telco partnerships cover networks reaching up to 99% of the UK population through 4G coverage and provide access associated with an estimated 78 million UK mobile connections. Around 53 million connections, it says, are available exclusively through Blis within advertising and marketing.

Those figures describe three different properties: population-level network coverage, mobile connections and exclusive access through a supplier. A person can have multiple mobile connections, while network coverage describes where service can reach people; an addressable advertising audience depends on which connections can be used for targeting. For a buying decision, teams should assess reach and exclusivity alongside the campaign outcome they require, defining the observed business performance and reliability over time that would justify adoption.

Key takeaways for decision-makers

• Start with data quality: In Blis-published research, 95% of surveyed UK marketers expressed significant concern about their data strategies’ longevity. Marketing decision-makers evaluating replacement signals need evidence of accuracy, commercial value and reliability over time.
• Audit audience inputs: While 78% linked source data quality to performance, only 48% trusted their existing inputs to meet accuracy standards. Marketing data owners can use this confidence gap to prioritize checks on the seed data used to build and expand audiences.
• Test telco signals against existing targeting: Telco-derived app usage and movement signals offer additional inputs for audience selection. Advertisers evaluating them can retain their current targeting setup and compare results with and without the added signals.
• Treat affinity gains as evidence of better alignment: Blis reported statistically significant category-affinity gains of 38% to 155% across five tested categories. Campaign owners need to establish whether comparable gains translate into conversions, revenue or return on advertising spend.
• Separate performance, durability and reach: Blis’s supplier-led research measures category affinity, while its coverage and connection figures describe potential network access. Buyers evaluating adoption need distinct evidence of addressable audience size, commercial performance and reliability over time.