Brysa flags a media-sector loyalty blindspot as acquisition costs jump

10 hours ago

By AI, Created 11:20 AM UTC, May 20, 2026, /AGP/ – Brysa says UK media businesses are overinvesting in new customer acquisition and underinvesting in retention, even as acquisition costs rise and repeat customers generate more value. The consultancy argues the gap is hurting profitability, predictability and client loyalty across the sector.

Why it matters: - UK media businesses are facing rising customer acquisition costs while failing to capture the higher value of repeat clients. - Brysa says that mismatch is cutting into profitability and making revenue harder to predict. - The consultancy frames retention as a structural growth issue, not a back-office problem.

What happened: - Brysa, a UK-based AI and data consultancy, identified what it calls a “loyalty blindspot” in the media sector. - The consultancy says media businesses keep prioritising acquisition over retention. - Brysa points to industry data showing acquisition costs have risen nearly 60% over the past five years. - Brysa says businesses are now losing an average of $29 on every new customer acquired. - Repeat customers spend 67% more than new customers. - A 5% improvement in retention can lift profits by 25% to 95%. - Brysa founder Satish Thiagarajan said media operators often focus on winning clients and then go quiet after a campaign ends.

The details: - Brysa says media businesses most often lose clients after the first sale in three places. - Poor onboarding and follow-through leave clients without clear alignment on goals, creative deliverables or success criteria. - Generic post-sale communication fails to reflect each client’s KPIs or strategic priorities. - Broken promises, missed deadlines and slow reporting erode credibility. - Brysa says the cost of weak retention is structural because acquisition spend keeps rising as competition intensifies. - Customer lifetime value falls when one-time clients do not become repeat buyers or referral sources. - Existing customers are 60% to 70% likely to buy again, compared with 5% to 20% for new prospects. - Campaign setup, creative production and reporting consume resources even when clients deliver limited ROI. - Brysa recommends four personalisation disciplines to close the loyalty gap. - Data-driven audience insight should use campaign history, audience demographics, performance metrics and seasonal trends to identify what resonates. - Customised campaign recommendations should match placements to each client’s audience, budget and objectives. - Brysa points to high-visibility billboard placements for awareness goals and contextual placements for hyperlocal reach. - Dynamic creative optimisation should adjust ad content in real time based on audience data or environmental conditions. - Brysa cites a beverage-brand example in which DOOH creative changes from hot coffee in the morning to cold brew in the afternoon. - Tailored reporting should replace standard performance summaries with insights tied to the client’s own success metrics.

Between the lines: - Brysa is arguing that media firms have borrowed audience-thinking for advertisers but have not applied the same discipline to their own client relationships. - The consultancy’s pitch is that better retention is not just more efficient, but more defensible as competition drives up acquisition costs. - The focus on personalisation suggests Brysa sees standardised post-sale processes as a reason clients drift to competitors.

What’s next: - Brysa is urging media leaders to audit post-sale engagement against its four personalisation disciplines. - The goal is to find where standardised workflows are creating transactional relationships instead of strategic ones. - The consultancy wants media businesses to rework retention before acquisition costs climb further.

The bottom line: - Brysa’s message is simple: media businesses are spending to win clients, but the bigger profit opportunity may be keeping them.

Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.

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