Marketing mix modeling (MMM) analytics solutions — Mark Stouse // Proof Analytics
- Part 1 Marketing mix modeling (MMM) analytics solutions — Mark Stouse // Proof Analytics
- Part 2Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics
- Part 3Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics (copy) (copy)
- Part 4Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics (copy) (copy)
Show Notes
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02:49Why its important for marketers to think about marketing mix modelingMarketing mix modeling is statistical analysis that helps marketers determine whats driving sales and how to optimize marketing investments. Marketers can also use it to forecast future sales based on historical data.
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09:52Marketing mix modeling vs multi touch attributionMulti-touch attribution isnt enough on its own, especially in the case of the deprecation of third-party data. Marketing mix modeling is the only statistically viable approach to show the value of marketing.
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10:56Datasets for B2B marketersStart with questions you want to answer, then look at the model that answers those questions. The problem marketing teams face is that they tend to collect a large amount of data that is pointless to the business.
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13:39Data that really mattersTop-of-the-funnel data is important. However, the data thats most significant shows the impact on the middle and the bottom of the funnel. So, the further you get down the funnel the more it becomes about risk mitigation.
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16:45What attribution looks like for established companies vs newer companiesIt really boils down to a companys budget, their goals, and the risks theyre trying to mitigate. For more established companies, the concerns are more operational while newer companies are trying to mitigate risks to their cash flow.
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19:29Where attribution models are going wrong for marketersThe challenge there is the lag of information in relation to multi-touch attribution. Its statistically impossible to use multi-touch attribution to optimize spend. So, multitouch attribution can only be valuable in a marketing mix modeling model.
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21:11How to build solid attribution modelsAs the marketer, you'll need to provide the contextual details for the model and for interpreting the model. Proof Analytics also has partners that will help you build these models, then it becomes an autonomous process afterward.
Quotes
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"Marketing mix modeling is the only statistically viable approach to showing the value of marketing." - Mark Stouse
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"The data that really matters is the data that shows your impact on the bottom of the funnel and on the middle part of the funnel." - Mark Stouse
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"At Honeywell, our biggest impact was at the bottom of the funnel. We got 12 billion of revenue moving five percent faster into the company. When you do that, the CFO becomes your best friend." - Mark Stouse
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"A lot of marketers tend to think of brand more in terms of what helps them at the top of the funnel. In reality, brand is a distillation of awareness, confidence, and trust in the customer." - Mark Stouse
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"The back half of the average funnel is all about risk mitigation in B2B. And the risk that's being mitigated by the customer is you, the vendor." - Mark Stouse
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"There are so many other ways to spend 120 million in a large company that they really need to know about that and always make an educated decision." - Mark Stouse
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"At Honeywell, the marketing budget was 160-170 million a year. If you spend that wrong, it has extended consequences for Honeywell, and the opportunity cost on that kind of money is huge." - Mark Stouse
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"We have a lot of partners that for 30-40 grand, over about a two-month period, will work with you to get 20 models built, start to run them for you. And then, it's fairly autonomous after that." - Mark Stouse
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"The license cost for Proof Analytics is $49 a seat per month on a monthly contract. So, we're seeking to be highly disruptive in this space for the benefit of the customer." - Mark Stouse
- Part 1 Marketing mix modeling (MMM) analytics solutions — Mark Stouse // Proof Analytics
- Part 2Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics
- Part 3Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics (copy) (copy)
- Part 4Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics (copy) (copy)
Up Next:
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Part 1Marketing mix modeling (MMM) analytics solutions — Mark Stouse // Proof Analytics
Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Marketing Mix Modeling or the MMM approach is based on a popular marketing theory known as the 4Ps of the marketing mix. The four elements of any successful business are product, price, place, and promotion, and marketers need to be able to measure the impact of their marketing and advertising campaigns. Today, Mark discusses marketing mix modeling.
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Part 2Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics
Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Even before the pandemic hit, Johnson Controls’ modeling predicted the economic decline and put them in the position to save a lot of money. Now, we’ve gotten to the point where marketing budgets are being slashed in half because of a lack of C-suite belief in marketers and the value they can bring to a company. Today, Mark discusses business data's underlying cause and effect relationships.
Play Podcast -
Part 3Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics (copy) (copy)
Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Even before the pandemic hit, Johnson Controls’ modeling predicted the economic decline and put them in the position to save a lot of money. Now, we’ve gotten to the point where marketing budgets are being slashed in half because of a lack of C-suite belief in marketers and the value they can bring to a company. Today, Mark discusses business data's underlying cause and effect relationships.
Play Podcast -
Part 4Business data’s underlying cause-and-effect relationships — Mark Stouse // Proof Analytics (copy) (copy)
Mark Stouse, CEO of Proof Analytics, talks about revenue-optimizing analytics solutions. Even before the pandemic hit, Johnson Controls’ modeling predicted the economic decline and put them in the position to save a lot of money. Now, we’ve gotten to the point where marketing budgets are being slashed in half because of a lack of C-suite belief in marketers and the value they can bring to a company. Today, Mark discusses business data's underlying cause and effect relationships.
Play Podcast
