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  3. Tracking Market Share Shifts with Alternative Data

Tracking Market Share Shifts with Alternative Data

Alternative data is very useful for tracking shifts in market share for digitally focused brands. In this guide, we will mainly work with Google Trends and Alexa web traffic data in Plotter.

First, access the Google Trends series:

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Let’s try tracking digital market share for Nike in the United States. First, select United States as your geographic region:

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Before entering the Google Trends brands, it is important to be aware of a key caveat: Google Trends values are expressed as a relative number to the maximum point of their returned time series. Because of this, it is important that you call multiple brands at the same time, so that their values are returned relative to the same data point. If you call them each individually, they will be returned relative to different data points, and will not be comparable.

To call the series for comparable analysis, enter all of the brands and separate them with commas as follows:

Screen Recording 2019-08-05 at 11.21.54.48 AM

After trying this for Nike, Adidas, and Under Armour, you should see the following:

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Now that you have added all of these series individually, you can simply use a hybrid series to obtain the market share for Nike:

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To obtain a proxy for Nike’s market share, we will simply take the Nike Google Trends series, and then divide it by the sum of all of the series that we are trying to compare (i.e. the “market”).

Screen Recording 2019-08-05 at 11.29.17.18 AM

You should see this:

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Now let’s hide all of the series and apply a moving average to smoothen out the market share series:

Screen Recording 2019-08-05 at 11.35.27.46 AM

Finally, let’s edit the name of our series and axis title:

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If you overlay NKE’s relative return to ADS:GR, you’ll see that the percent share of Google Trends is very closely related to the relative performance of the stocks:

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Alexa Web Traffic

Alexa web traffic data is also very useful for capturing market share shifts. Let’s try an example with Carvana and Carmax. To start, simply add the url’s carmax.com and carvana.com in the same input box. Unlike with Google Trends above, you can plot these as separate plotter calls and they will still be comparable to each other. We still recommend entering them together for a faster workflow:

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Now go to hybrid series, and enter A/(A+B) as your formula:

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Now apply a moving average, and rename your series to make for a more presentable chart:

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Finally, try plotting the relative returns for CVNA over KMX:

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Notice that CNVA started outperforming KMX once its relative share of web traffic started to inflect.

Conclusion

While predicting beats and misses is a top use case for alternative data, tracking market share shifts is also very powerful and often underlooked. Please reach out to Sentieo support if you require further assistance as you set up your own market share charts.

Updated on August 5, 2019

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