<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Manolis_in_data]]></title><description><![CDATA[I help startups and scaleups understand what drives their revenue and how to grow more efficiently. By connecting marketing, product, and sales data, I identify revenue drivers, uncover performance gaps, and provide clear, actionable insights to improve decision-making, marketing efficiency, and overall growth.]]></description><link>https://www.manolisindata.com/blog</link><generator>RSS for Node</generator><lastBuildDate>Fri, 17 Apr 2026 09:49:48 GMT</lastBuildDate><atom:link href="https://www.manolisindata.com/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Key Startup KPIs for Revenue Growth]]></title><description><![CDATA[Tracking the right key performance indicators (KPIs) is essential for startups aiming to accelerate revenue growth. Without clear metrics, decision-making becomes guesswork. I focus on KPIs that provide actionable insights and directly impact the bottom line. This approach helps identify strengths, weaknesses, and opportunities for improvement. Startups often struggle with scattered data. Organizing and analyzing this data through relevant KPIs turns it into a powerful tool. It guides smarter...]]></description><link>https://www.manolisindata.com/post/key-startup-kpis-for-revenue-growth</link><guid isPermaLink="false">69d934aab1404b5ae2d61e76</guid><pubDate>Mon, 13 Apr 2026 06:00:08 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_c9bf36d7cdf144c2845a743f07a17ddd~mv2.png/v1/fit/w_1000,h_576,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Emmanouil Vryonakis</dc:creator></item><item><title><![CDATA[Why Most Companies Don’t Have a Growth Problem, They Have a System Problem]]></title><description><![CDATA[Growth rarely breaks in obvious ways. It does not suddenly stop. It slows down gradually. Conversion rates plateau, acquisition costs increase, and new channels fail to scale the way they once did. Teams respond by pushing harder on what they can control, launching more campaigns, running more tests, investing in new tools. The assumption is that growth is a function of effort. In reality, growth is a function of systems. Most companies do not lack ideas, traffic, or even budget. What they...]]></description><link>https://www.manolisindata.com/post/why-most-companies-don-t-have-a-growth-problem-they-have-a-system-problem</link><guid isPermaLink="false">69d94702b1404b5ae2d64aa7</guid><category><![CDATA[Growth Strategy]]></category><pubDate>Tue, 07 Apr 2026 21:00:00 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_29986db8b9534ad7b357c789d871716f~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[LTV Is Not a Number, It Is a Model]]></title><description><![CDATA[Lifetime value is one of the most frequently cited metrics in growth discussions, yet it is also one of the least understood. In many organizations, LTV exists as a single number in a dashboard. It is referenced in presentations, used to justify acquisition spend, and occasionally compared against cost per acquisition to assess efficiency. On the surface, this seems sufficient. A higher LTV suggests a healthier business, and a favorable ratio between LTV and CAC implies scalability. The...]]></description><link>https://www.manolisindata.com/post/ltv-is-not-a-number-it-is-a-model</link><guid isPermaLink="false">69d93e8af6703ec22beaa4b3</guid><category><![CDATA[Growth Strategy]]></category><category><![CDATA[Attribution Modeling]]></category><pubDate>Wed, 01 Apr 2026 21:00:00 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_41b02dd495854a03b65ad17c4122e337~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[Why Your CAC Looks Fine, But Your Business Isn’t Profitable]]></title><description><![CDATA[There is a recurring pattern across growth-stage companies. Acquisition appears to be working, dashboards show stable performance, and cost per acquisition sits within what most teams would consider an acceptable range. Campaigns are scaled with confidence, budgets increase, and yet profitability remains elusive. At first glance, this seems contradictory. If acquisition is efficient, the business should grow sustainably. In practice, the opposite often happens. The issue is not that CAC is...]]></description><link>https://www.manolisindata.com/post/why-your-cac-looks-fine-but-your-business-isn-t-profitable</link><guid isPermaLink="false">69d93d7946e8409f60b16706</guid><category><![CDATA[Growth Strategy]]></category><category><![CDATA[Attribution Modeling]]></category><pubDate>Mon, 30 Mar 2026 21:00:00 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_ec10b00485f64dc98fcbf0a02ab50f16~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[Reducing CAC by 30 Percent: A System Approach to Experimentation and Attribution]]></title><description><![CDATA[Cost per acquisition rarely increases because of a single mistake. More often, it drifts upward gradually, the result of small inefficiencies accumulating across channels, messaging, and user experience. By the time it becomes a visible problem, it is already embedded in the system. This was the situation for a mid sized ecommerce brand operating across multiple paid channels. Performance was deteriorating, but not in a way that pointed to an obvious cause. Conversion rates were stable,...]]></description><link>https://www.manolisindata.com/post/reducing-cac-by-30-percent-a-system-approach-to-experimentation-and-attribution</link><guid isPermaLink="false">69d934b8515c02011a0c253d</guid><category><![CDATA[Attribution Modeling]]></category><pubDate>Thu, 26 Mar 2026 18:36:23 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_046169b4febf438bace2ba2721497da9~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[Why Data Warehousing Is the Foundation of Modern Growth]]></title><description><![CDATA[Most companies do not struggle because they lack data. They struggle because their data exists in fragments that cannot be reconciled into a coherent picture. Analytics dashboards multiply, reports become inconsistent, and different teams operate with different versions of reality. Marketing sees one set of numbers, product sees another, finance trusts neither fully. Decisions are still being made, but they are made with hesitation, often shaped more by intuition than by evidence. This is not...]]></description><link>https://www.manolisindata.com/post/why-data-warehousing-is-the-foundation-of-modern-growth</link><guid isPermaLink="false">69d9342ab1404b5ae2d61d27</guid><category><![CDATA[Data Systems]]></category><pubDate>Thu, 19 Mar 2026 18:33:58 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_3e5543e4e6e743e5abe10e5039284b86~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[The Hidden Cost of Winning A/B Tests]]></title><description><![CDATA[Most A B tests are evaluated the same way. A variation outperforms the control, conversion rate increases, and the test is declared a success. The result is shipped, documented, and added to a growing list of “wins”. On paper, this looks like progress. In reality, many of these wins are misleading. The core issue is not with experimentation itself, but with how success is defined. When tests are judged primarily on conversion rate, they optimize for immediate action, not long term value. This...]]></description><link>https://www.manolisindata.com/post/the-hidden-cost-of-winning-a-b-tests</link><guid isPermaLink="false">69d93faef6703ec22beaa773</guid><category><![CDATA[A/B Experimentation]]></category><pubDate>Sat, 28 Feb 2026 22:00:00 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_6482f4ec8a0047c5aed306839577ecd9~mv2.jpg/v1/fit/w_1000,h_929,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[From Channel Chaos to Strategy: Rethinking Attribution in a Multi Touch World]]></title><description><![CDATA[Most marketing teams operate with a distorted view of reality. Not because they lack data, but because they rely on models that simplify behavior to the point of being misleading. Attribution is where this distortion becomes most visible. In many organizations, performance is still evaluated through last click attribution. The final interaction before conversion receives full credit, while everything that influenced the decision before that moment is either ignored or undervalued. On the...]]></description><link>https://www.manolisindata.com/post/from-channel-chaos-to-strategy-rethinking-attribution-in-a-multi-touch-world</link><guid isPermaLink="false">69d933964750526d40bd1534</guid><category><![CDATA[Attribution Modeling]]></category><pubDate>Thu, 19 Feb 2026 18:31:40 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_ae37fe96c6be457cab71d5063251583f~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[Beyond A/B Testing: Experimentation as a Revenue Engine]]></title><description><![CDATA[For most companies, A B testing exists at the edge of the business. It is treated as a tactical layer, something that improves conversion rates incrementally, occasionally producing small wins that look good in reports but rarely change the trajectory of growth. That framing is fundamentally limiting. At scale, experimentation is not about optimization, it is about decision making under uncertainty. The difference is subtle but critical. When teams approach testing as a way to tweak existing...]]></description><link>https://www.manolisindata.com/post/beyond-a-b-testing-experimentation-as-a-revenue-engine</link><guid isPermaLink="false">69d931b761f85fcf9f7c258b</guid><category><![CDATA[A/B Experimentation]]></category><pubDate>Thu, 29 Jan 2026 18:27:41 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_e154268f560a4eada0dde2afc5805f53~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item><item><title><![CDATA[From Data Chaos to Insight Driven Growth]]></title><description><![CDATA[Growth slows down long before companies realize it. Not because demand disappears, but because clarity does. At a certain stage, most organizations accumulate enough tools, dashboards, and reports to feel data rich. Marketing platforms provide detailed performance metrics, analytics tools track user behavior, CRM systems capture customer interactions. On the surface, everything required to make informed decisions is already in place. Yet decisions become harder, not easier. Different teams...]]></description><link>https://www.manolisindata.com/post/from-data-chaos-to-insight-driven-growth</link><guid isPermaLink="false">69d935374750526d40bd193f</guid><category><![CDATA[Growth Strategy]]></category><pubDate>Sun, 04 Jan 2026 18:38:48 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/7466e2_3036aba12f964a85ad84485522f21f47~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Manolis</dc:creator></item></channel></rss>