Website Geo-Targeting as a Forecasting and Budgeting Tool

September 3, 2010
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Capturing an individual’s postal or zip code on a website form can provide valuable information for forecasting sales and planning budgets. A website can be utilized to capture the postal or zip code of its visitors: when a product is purchased, a ‘contact us’ form is completed or a white paper is downloaded. This information can then be combined with ‘cookie data’ to produce reports that summarize the unique number of visitors to a website (for any purpose, or by specific reason of visit) for a geographic area – FSA, postal code, enumeration area, or census tract.

Capturing an individual’s postal or zip code on a website form can provide valuable information for forecasting sales and planning budgets. A website can be utilized to capture the postal or zip code of its visitors: when a product is purchased, a ‘contact us’ form is completed or a white paper is downloaded. This information can then be combined with ‘cookie data’ to produce reports that summarize the unique number of visitors to a website (for any purpose, or by specific reason of visit) for a geographic area – FSA, postal code, enumeration area, or census tract. Data from Statistics Canada or third party vendors such as Generation5, Environics Analytics and MapInfo may then be appended to this report: population counts by age and average annual household expenditure estimates, for example.

Once consolidated, this information can be utilized in forecasting revenue and planning marketing budgets:

1. A rough ‘penetration rate estimate’ (PENETRATION RATE) for each geographic area can be calculated by dividing the number of unique website visitors who entered postal/zip code data by Statistics Canada’s total population data for the area in question.

2. Population and expenditure growth history data for each area may be used to estimate population (POPULATION ESTIMATE) and household expenditure (HOUSEHOLD EXPENDITURE) levels in future years. These estimates might be projected using any one of the following regression techniques that can be found in spreadsheet applications and sophisticated modeling software: linear, logarithmic, polynomial, exponential, power, or moving average.

3. An estimate of the potential revenue (POTENTIAL REVENUE) to be gained in each geographic area of interest could be determined using (POPULATION ESTIMATE) and (HOUSEHOLD EXPENDITURE) data.

4. Knowledge regarding the website owner’s overall current market share (based on market research) may be applied to determine the expected MARKET SHARE of each area’s POTENTIAL REVENUE that could be generated via a marketing campaign.

5. Finally, marketing campaign cost assumptions can be compared to the MARKET SHARE estimate in order to determine a potential marketing campaign return on investment (ROI) for each geographic area to be targeted.

Before a marketing campaign is actually conducted, geo-demographic, behavioural and attitudnal data may also be accessed to better understand populations residing in each of the geographic areas that are to be targeted.