Automotive Analytics

DATA SOURCES

Nielsen

o AMRLD

o AdView

o NOL

o Buzz Metrics

o IAG

Social

o FanPage

o FaceBook

o Twitter

o Pinterest

o Karma

o Klout

Web

o Google Analytics

o ComScore

o Flurry

o MixPanel

Other

o CRMs

o ERPs

o Xcel

o GPS

o POS

o Census

Kovariant provides a broad range of modeling and analytic services available to help our Automotive clients increase sales and revenue.  Working with your team, Kovariant can apply any number of existing models or help you design new models to effectively answer today’s most challenging multichannel marketing questions.   Below are few examples of modeling we support:

 

Dealerships

New Customer Acquisitions

  • Understand and maximize customer response, activation and cross-selling opportunities
  • Segmentation models that increase marketing effectiveness and increase ROI
  • Profiles, profile models, and response models including active comparison of your customers to national data.
    • Compare your best customers to a national data set to create a model
    • Construct response models to inquiries and construct a model for ideal responders

Market Spending Efficiency

  • Utilize custom models to reallocate or reduce marketing spend:
  • Apply response performance indicators to any customer or prospect data file.
  • Tailor mailings based on model qualified candidates
  • Prospect ranking based on ecommerce data and RPI ranking

Market Ready Models

  • Utilize statically modeled values to indicate a household’s inclination to purchase a vehicle in the near term.
  • Predict response rate to direct or digital marketing.

OEM Manufacturers

Through customer sales, incentive and brand modeling, Kovariant helps OEMs better understand how they can maximize their budgets, how to allocate their marketing spend, better understand upper and lower funnel actions, impact of cross media, social media, and mobile.   Asking better questions can often lead to better insight in to what is driving KPI’s, and the cumulative effect of today’s multi-channel advertising.

  • Media Buyer Performance
  • Brand vs Market Segmentation
  • Marketing Mix Optimization
  • Campaign ROI
  • Incentive ROI
  • Econometric Modeling
  • Web analytics to measure a wide variety of KPI’s (i.e. Who visited, what page did they visit, did they buy, or did request information, etc.)
  • Recency reports ( TV Ad to Web KPI)

 

Why Multichannel Analytics?

“Multichannel customers spend three to four times more than single channel customers.”

Multichannel Marketing is the practice of interacting with customers using a combination of indirect and direct communication channels – websites, retail stores, mail order catalogs, direct mail, email, mobile, etc. – allowing customers to use the channel of their choice when engaging with a product, service or content.

 

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Data Customization

The foundation to better analytics is knowing how to ask the better questions, but first you need to figure out what are you trying to answer. Knowing all the data resources you have available and being able to utilize them in unison is the key to powerful analytics. The more data you have available – the more questions you can ask, but when merging all these resources together – the better questions you will ask, which translates to the better answers you will have.

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