Why Rows > Columns in MMM

If your job involves dealing with tabular data, then it is always prudent to ask for more data (rows) rather than ask for more features (columns).

There is no point in having more columns which are shallow (i.e. missing data).

We at Aryma Labs deal with tabular data a lot, especially in the form Marketing Mix Model (MMM) data.

Whenever client provides us data and asks the question “Are the data enough or should we get more features?”

We always ask them if they can provide more rows than columns.

Statistically speaking too, having more rows is better because the chances of you estimating the coefficients with less bias is more.

Less number of rows per columns always pose the risk of higher bias and there by leading to model misspecification.

Marketing Mix Modeling, Media Mix Modeling, Marketing Effectiveness, Experimentation, Causal Inference, Adstock, Marketing ROI, Statistics, Machine Learning, Marketing Attribution, Media Planning, Marketing Budget Optimization, Robyn, Multi touch Attribution, First Party Data, Privacy Proof Marketing Solutions.

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