Due to an online-offline advertising saturation, Chevrolet is open to try new formats and ideas.

We wanted to demonstrate that the purchase of a car made by a neighbor, increases the decision to buy a car in people around him.

Rise the sales in the area with a much smaller budget.

Be the plot point for a n ew way of advertising.

Demonstrate that data and human behavior can turn into a great tool to sell cars.

First, our data scientists extracted real-time feedback on sales, discovering our best-selling car is the blue Aveo, and mapping the area in Mexico City where more blue Aveos are sold and, as a consequence, where our potential future buyers would be.

Then, we created an online and offline virtual fence around them, cross-matching with Google Maps data to get the streets, avenues and places of greater activity and higher relevance to announce a promotion tailored to this trend.

We placed our ads in the busiest car wash, the hottest pizza place, the biggest laundromat, gyms, drugstores, cafeterias, diners, barber shops and all of the most relevant spots of the area.

On digital media, our message was geotargeted to appear within this higher-influence area.

Every single piece developed offered a special discount: The last nudge for an already predisposed target.

We gather Data from 6 different sources both 1st party and 3rd party.

1st party data:

1. Sales data 2018 - 220,000 sales analyzed consist in:

- Date: Sale, invoice, delivery

- Cars Data: Model, Year, Version, Color, Price

- Dealers information: Type, Name, Location, City, Address

- Owners information: Address, gender, age, contact info.

- Financial: Cash, Credit, Leasing, Promotion

2.- years Sales Data up to 2,000,000 sales analyzed from 2010 to 2017 – Same info: Date, Cars, Dealers & Owners (different analysis)

We analyzed all 2018 sales information in order to find the best-selling car, city, zone & color.

We discarded non-relevant information: Fleets, Company’s Purchases, demos, etc.

Through an analysis of variations related to the average we discarded zones with atypical behaviors or non-relevant to the target.

Zone & Potential Customers: Our primary target was the population in the zone obtained from the 2018 data analysis. Socio-economic level similar to current owners

CRM: Our secondary target for CRM was Chevy car owners in their re-purchase period and had bought a car model with strong relationship with the one we were advertising – AVEO

Small business related to defined potential customers and customers in re-purchase period.

-Our implementation took place in the busiest car wash, the hottest pizza place, the biggest laundromat, gyms, drugstores, cafeterias, diners, barber shops and all of the most relevant spots of the area.

-Outdoor.

-January and March 2019.

-Small Scale.

145% Increase in sales within the area.

186% Above sales outside the area.

Spending only 25% of the regular investment.