Geographic Analysis Insights with Google Analytics

Geographic Analysis Insights with Google Analytics

Towards the end of 2015, one of our existing clients requested a more granular data analysis that would reveal insights about their target audience’s geographic location. Specifically, our client wanted to see which cities were generating the most impressions and which zip codes were generating the most leads for our successful PPC campaign.

Lucid Agency started by determining which cities were triggering the most traffic to the website. Using the Google Analytics Audience report, we were able to analyze data at the city level. We looked at all-time data in order to observe changes over time in total traffic per business quarter. Our presentation to the client included a proportional circle map indicating the relative amount of traffic in each major city. The result looked similar to this example (our client’s data is confidential, so we cannot show the actual results):

figure-1-ga

Our preliminary analysis revealed that there were three primary cities bringing the most traffic to the website. We have adjusted the budgets for our 2016 online ad campaign accordingly, to focus on the cities with the best results and to delegate less budget to the underperforming cities.

Next, we set out to discover which zip codes were producing the most leads, and to present these results to our client in a meaningful way. For this, we determined that a heat map would be the most effective visual representation.

We started by exporting the necessary zip code data from Google AdWords. The data included converted clicks, clicks, and impressions for each of the zip codes in which we were placing PPC ads. In order for Google Maps to pinpoint each of the zip codes on the map, we cross-referenced the latitude and longitude coordinates for each zip code, and added that data to the spreadsheet. Then, we uploaded this information into a Google Fusion Table, specified the “Location” data, and added a city map. Finally, we used these instructions as a guide to create a heat map overlay that displayed the zip codes with the most converted clicks. The result looked similar to this (again, the real data may not be shared):

heat-map

This heat map was an important visualization that easily represented which zip codes had the highest conversion rate and which zip codes were “cold” or not generating conversions as efficiently. This map informs Lucid Agency’s targeted zip codes for the PPC campaign in 2016.

Finally, we used these findings to come up with a series of recommendations for the client. First, as mentioned, we were able to confidently adjust our budget allocations to focus on the highest-performing cities, and moved budget away from the targeted cities that were not converting. This allowed us to optimize lead flow and cost. Lucid also recommended cross referencing lead conversion data with sales data (by zip) to find out which zip codes most often result in an actual sale, and to adjust the marketing strategy accordingly.

Lucid Agency is hoping to apply both of these recommendations in 2016, and we will reevaluate our geographic targeting at the end of 2016, now that we have all the tools we need to re-implement this analysis in the future.

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