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SmartData Collective > Big Data > Data Mining > The Geography of Telecommunications Marketing
Data Mining

The Geography of Telecommunications Marketing

TeradataExperts
TeradataExperts
5 Min Read
The Geography of Telecommunications Marketing
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
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Years ago, when I was helping start up a local phone company and later starting up a local cable company, I became aware of how “local” these giant businesses can be. Local can drive everything from pricing to network to advertising. I spent several years working on state level pricing in telecom and the difference between two neighboring states could be enormous.

So I was really excited about the geospatial aspects of Teradata 13. For years, CMOs and marketing analyst have been constrained from really understanding the local impact of decisions. With too much data and under-served by analysis and visualization solutions, the CMO has had to make do with limited information in understanding local market trends and the influence of local factors on performance.

Mash-ups with Google Earth just can’t deliver the insight needed. George Salvador from Time Warner Cable just did an interview with LBx Journal where he talked about six ways geographic data can be used better in the cable space. By the way – LBX Journal is a cool new magazine on the use of location data for businesses. (Disclaimer, I have worked and think highly of its publisher Natasha Leger)

One geospatial challenge facing Communications, CMOs is that much of their offline advertising is based on local spend – radio, TV, newspaper. Much of the result of that advertising may end up in an online search or online purchase. And other results could be in local store visitors and purchases.

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How does the CMO tie all this together to understand the true impact of their advertising spend. With Teradata Integrated Web Intelligence we can bring these disparate data types together into a geographic data set. Local AD spend, Search and Online Advertising geographical information, store traffic and web site results segmented by geography.

The resulting analysis starts to tie the trail of an advertising dollar, euro or peso into an acquisition, upsell or cross-sell. Loyalty is also influenced by these factors – as well as local competitive influences. Here are some questions I think can be answered with this approach – can you send me more?

  • How does local ad spend correlate to the local search frequency / clicks?
  • Does local search activity tie to local store traffic, sales and product selecting?
  • How do online ads on local sites tie to local store traffic?
  • How do competitive factors influence local sales performance?
  • Does the quality of the carriers’s network impact search activity geographically?

Let me know if you have other ideas how to use this data?

Paul Barrett

TAGGED:geographic data
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