{"id":8938,"date":"2026-10-17T23:36:08","date_gmt":"2026-10-17T20:36:08","guid":{"rendered":"https:\/\/ivitskiy.com\/blog\/?p=8938"},"modified":"2026-10-17T23:40:37","modified_gmt":"2026-10-17T20:40:37","slug":"smx-advanced-europe-2026","status":"publish","type":"post","link":"https:\/\/ivitskiy.com\/blog\/en\/smx-advanced-europe-2026\/","title":{"rendered":"The Lies Your Data Is Telling You: Igor Ivitskiy at SMX Advanced Europe 2026"},"content":{"rendered":"\n
In short:<\/strong> At SMX Advanced Europe 2026 in Berlin, Igor Ivitskiy showed how large Google Ads accounts mislead their owners: a stable CPA hides shrinking acquisition, ROAS grows while a warmer audience does the work, and a target met on average hides losing product groups. He packed it into nine lessons in three groups (the number, the buyers, the money) and nine fixes. The core rule: before you believe any number, ask which question it actually answered.<\/div>\n\n\n\n

SMX Advanced Europe 2026<\/a>, the vendor-independent expert-level search conference, took place on September 30, 2026, in Berlin, at the Meli\u00e1 Hotel. In the PPC track of day two, Igor Ivitskiy<\/a>, PhD in mathematical modeling and founder of Doctor Ads, took the stage in hall Barcelona 2.<\/p>\n\n\n\n

<\/span>\"Igor
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Stop asking which number is true. Ask which question it answered.<\/strong><\/p>\n<\/div><\/div>\n\n\n\n

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Conference<\/strong><\/td>SMX Advanced Europe 2026 (Rising Media)<\/td><\/tr>\n
Date<\/strong><\/td>September 30, 2026<\/td><\/tr>\n
City and venue<\/strong><\/td>Berlin, Germany, Meli\u00e1 Hotel Berlin<\/td><\/tr>\n
Session<\/strong><\/td>PPC track, day two, 15:00\u201315:45, hall Barcelona 2, moderated by Anu Adegbola (Search Engine Land, PPC Live UK)<\/td><\/tr>\n
Talk<\/strong><\/td>«The Lies Your Data Is Telling You: 6 Statistical Failure Modes in Large-Scale Google Ads»<\/td><\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n

The talk was built for the audience SMX Advanced is known for: specialists from large companies running serious budgets, people who already know how campaigns work and want to know why the numbers still mislead them. Igor packed 19 years of Google Ads into nine lessons: «Nine lessons I paid for, and you can use it without spending budget on these lessons.» Most examples on screen were worked examples with made-up numbers and realistic proportions, so the patterns matter more than the exact figures.<\/p>\n\n\n\n

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Few competitors bid on your name<\/strong><\/div>\n
<\/div><\/div>\n
\u20ac9 of \u20ac100 brand-ad revenue is thanks to the ad<\/div>\n<\/div>\n
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3+ competitors bid on your name<\/strong><\/div>\n
<\/div><\/div>\n
\u20ac37 of \u20ac100 is thanks to the ad<\/div>\n<\/div>\n<\/div>\n
Source: SMX Advanced Europe 2026, Igor Ivitskiy. Worked example: \u20ac100 of brand-ad revenue as Google Ads reports it, split by how many competitors bid on the brand name; proportions from Haus geo experiments on brand search.<\/div>\n\n\n\n

Same numbers, different picture, different decision<\/h2>\n\n\n\n

One business, one month, five systems: Google Ads shows ROAS 6.1, GA4 shows 3.8, the CRM says 4.4, the attribution tool claims 5.2, and finance counts 3.1. The first reflex is that something is broken. Igor opened with a gentler example: he had checked three weather websites for Berlin that same day, and they promised sun, heavy rain and clouds at once. They are not broken. They use different methodologies to process the same data, and each dashboard answers its own question honestly.<\/p>\n\n\n\n

Then he moved to Anscombe’s quartet, four data sets built by statistician Francis Anscombe in 1973. All four share the same trend line, y = 3 + 0.5x, the same R\u00b2 of 0.67 and the same mean, yet the raw points behind them tell four completely different stories, and each story demands a different decision. That is the spine of the whole talk: the summary statistic can stay identical while the reality underneath it changes completely.<\/p>\n\n\n\n

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1<\/span>The number: is it real?<\/strong>
Winners chosen by luck, significance stars that measure data size rather than profit, and modeled conversions quietly reshaping market rankings.
Ask: would this winner win again, and how much of this number is a model’s guess?<\/div><\/div>\n
2<\/span>The buyers: who is behind it?<\/strong>
A stable CPA can hide shrinking acquisition, a rising ROAS can hide a warmer audience mix, and a promo spike can be borrowed from the next two weeks.
Ask: what does a new customer cost, and did buyers buy more or just earlier?<\/div><\/div>\n
3<\/span>The money: where should the next euro go?<\/strong>
Brand ads judged without competitor pressure, targets met on average while parts of the budget burn, and budget plans built on average ROAS.
Ask: who is losing inside the average, and what will the next euro actually bring?<\/div><\/div>\n
4<\/span>Nine fixes for Monday<\/strong>
Every lesson ends with a rule for a decision: who gets extra budget, when to stop scaling, which brand campaign to pause-test first. The mechanics of each rule are walked through in the full recording.
Ask: which of the nine questions will you ask your own data first?<\/div><\/div>\n<\/div>\n
Source: SMX Advanced Europe 2026 talk, Igor Ivitskiy.<\/div>\n\n\n\n

Stop asking which number is true. Ask which question it answered, because same numbers can have different pictures and different decisions.<\/p>Igor Ivitskiy, SMX Advanced Europe 2026<\/cite><\/blockquote><\/figure>\n\n\n\n

My rule after 19 years in Google Ads<\/strong><\/p>

My biggest point is always the same: never look at the whole number, always dive deeper into detail. A difference in the shares between a few subsystems inside one campaign can change the result in a completely unexpected way, so I split the data before I believe it.<\/p><\/section>\n\n\n\n

This way of reading an account, evidence first and dashboards second, is what Igor teaches his students: split the data before you trust the total.<\/p>\n\n\n\n\n\n\n\n

Key insights<\/h2>\n\n\n\n