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Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl. cover
Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl. cover
The Bridge by Artefact

Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl.

Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl.

05min |19/12/2023
Play
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Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl. cover
Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl. cover
The Bridge by Artefact

Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl.

Interview "The Bridge" about MMM with Sid Mohan, Data Science Dir. & Global Lead Causal AI Research & MMM at Artefact - Data Coffee in Engl.

05min |19/12/2023
Play

Description

In this video interview, Siddharth Mohan, Director Data Science & Global Lead for Causal AI Research & Marketing Mix Modelling at Artefact, explains the three methodologies (attribution, incremental testing, and marketing mix modeling, or MMM) that comprise the marketing measurement framework.

Attribution, incremental testing and MMM currently face constraints preventing seamless collaboration.

- The attribution model needs to incorporate constraints which contextualize the baseline, critical to understanding the overall impact of marketing activities.

- Incremental testing often necessitates advanced techniques like Bayesian Causal Inference and the Potential Outcomes Framework to remove confounding effects.

- In MMMs, there are solid opportunities to leverage the latest advances in Structured Causal Models.


Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Description

In this video interview, Siddharth Mohan, Director Data Science & Global Lead for Causal AI Research & Marketing Mix Modelling at Artefact, explains the three methodologies (attribution, incremental testing, and marketing mix modeling, or MMM) that comprise the marketing measurement framework.

Attribution, incremental testing and MMM currently face constraints preventing seamless collaboration.

- The attribution model needs to incorporate constraints which contextualize the baseline, critical to understanding the overall impact of marketing activities.

- Incremental testing often necessitates advanced techniques like Bayesian Causal Inference and the Potential Outcomes Framework to remove confounding effects.

- In MMMs, there are solid opportunities to leverage the latest advances in Structured Causal Models.


Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

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Description

In this video interview, Siddharth Mohan, Director Data Science & Global Lead for Causal AI Research & Marketing Mix Modelling at Artefact, explains the three methodologies (attribution, incremental testing, and marketing mix modeling, or MMM) that comprise the marketing measurement framework.

Attribution, incremental testing and MMM currently face constraints preventing seamless collaboration.

- The attribution model needs to incorporate constraints which contextualize the baseline, critical to understanding the overall impact of marketing activities.

- Incremental testing often necessitates advanced techniques like Bayesian Causal Inference and the Potential Outcomes Framework to remove confounding effects.

- In MMMs, there are solid opportunities to leverage the latest advances in Structured Causal Models.


Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Description

In this video interview, Siddharth Mohan, Director Data Science & Global Lead for Causal AI Research & Marketing Mix Modelling at Artefact, explains the three methodologies (attribution, incremental testing, and marketing mix modeling, or MMM) that comprise the marketing measurement framework.

Attribution, incremental testing and MMM currently face constraints preventing seamless collaboration.

- The attribution model needs to incorporate constraints which contextualize the baseline, critical to understanding the overall impact of marketing activities.

- Incremental testing often necessitates advanced techniques like Bayesian Causal Inference and the Potential Outcomes Framework to remove confounding effects.

- In MMMs, there are solid opportunities to leverage the latest advances in Structured Causal Models.


Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Share

Embed

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