METHODOLOGY FOR BORRELL DATA Borrell Methodology 11/30/2011.

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Presentation transcript:

METHODOLOGY FOR BORRELL DATA Borrell Methodology 11/30/2011

The Borrell Ad Spend Model  Under continuous development since 1984  NAA Lifetime Achievement Award to chief architect Kip Cassino, Executive Vice-President  In long-term use by major media companies  Advertiser-centric rather than media-centric  Bottom-up rather than top-down  Based on multiple sources

…measuring ad spending would be easy If the world had only one market… If the world only had one market…

…markets are all over the place. Unfortunately… If the world only had one market…

Ad spending generated in a market… …may go anywhere. Ad spending from any other market may end up in the market you’re trying to measure.

How we do it… Borrell separates ad spending that’s coming in from ad spending going out… So, we can measure: Ad spending generated in a market. Ad spending generated in a market. Ad spending directed to a market Ad spending directed to a market from someplace else. from someplace else. Ad spending generated and spent Ad spending generated and spent locally. locally.

We start with two databases… #1 - Estimates ad spending by more than 20 million US companies #2 - Estimates receipts for all US Media Companies

At the National Level… 1 = 2 ! That is, total US ad spending must equal total receipts for US media companies. =

Database 1 (Spending) Sources… Dun & Bradstreet (updated quarterly) Dun & Bradstreet (updated quarterly) IRS IRS The Postal Service The Postal Service Annual reports & 10K’s Annual reports & 10K’s More than 40 additional secondary More than 40 additional secondary sources (magazines, association reports, sources (magazines, association reports, surveys, articles), including – surveys, articles), including – Editor & Publisher, Advertising Age, etc. Editor & Publisher, Advertising Age, etc.

We don’t stop here! Every company’s spending estimate is modified to fit specific markets in two ways.

Two Modifications First, every estimate is altered to fit the media demand pattern of its specific market, using data from: Nielsen, Scarborough, Demographics Now, Claritas and other sources. Second, the estimates are not expressed as percent of revenue… but as Per Employee ad expenditures.

In general ad spending increases as businesses get larger… …the per employee percentage of ad spending actually drops. drops. Each SIC has its own distinct pattern. We measure and account for that. But… Employees are key! % $

Database 2 (Receipts) Sources… Dun & Bradstreet Dun & Bradstreet Annual reports & 10K’s Annual reports & 10K’s More than 40 additional secondary More than 40 additional secondary sources (magazines, association reports, sources (magazines, association reports, surveys, articles), including – surveys, articles), including – NAA RAB DMA TVB IAB YPPA Media Week, OMMA, Advertising Age, Our own survey of media company revenues with 4,800+ companies represented.

Comparisons Made Each media estimate is compared to other sources (including McCann Erickson, Veronis Suhler, Jupiter, Forrester and others) to insure accuracy. When discrepancies are found, that are not due to methodology or definitions, the estimates are re- computed.

Once the two databases agree… … the resulting estimates (by SIC and media choice) are distributed to all US counties. distributed to all US counties. Distribution to counties is a three-step procedure:

Once the two databases agree… Step 1: Allocation Media estimates are allocated to each county using the weighted values of several variables, including: households households retail sales retail sales median income median income gross regional product gross regional product population population median age median age Step 2: Replacement Whenever possible, allocated estimates are replaced by actual known information. Typically, about 25% of the estimates are replaced. Step 3: Recalculation After replacement, the sum of the estimates will no longer foot to the original national totals. So, all un-replaced estimates are indexed and recalculated.

To complete a market estimate, we must return to Database 1 – Ad spending estimates for every US business. Not yet! All of our work so far has produced estimates of ad spending directed to each market. We still don’t know how much is local. Is it Soup yet?

Estimates from Database 1 Estimates from Database 2 The first contains the ad spending generated in the measured market. The second contains ad spending directed to the market. Think of three Glasses…

The contents of both must be “poured”… “poured”… …into the third glass – which represents ad spending in the measured market. …poured into one

For some media, the contents of the first two glasses will not fill the third. More ad spending must be “imported” to make up the difference. Imports

For some media, the contents of the first two glasses will more than fill the third. The ad spending “overflow” must be “exported” to other markets. Exports

The Formula is Simple Ad Spending generated in a market (Database #1) - “Exports” + “Imports” MUST = Ad Spending directed to a market

Used by many of the nation’s largest Used by many of the nation’s largest Media Companies for years. Media Companies for years. Used by Advo, TV networks, ad Used by Advo, TV networks, ad agencies, telecommunications companies… agencies, telecommunications companies… Has shown to be accurate to within Has shown to be accurate to within 3-5 percent In markets where 3-5 percent In markets where we can get “on the ground” evidence. According to Booz Allen: “Only According to Booz Allen: “Only methodology that could work.” methodology that could work.” How good is the Result?

What they’re saying….  “Accurate enough to be actionable” − Borrell client  “Solid guidance on scale and direction” − Another Borrell client

Our Model in Action - Examples  Political Ad Spending  Borrell Projected $20 million  Competitors projected $75 million  Actual was $19.5 million  Directories  Projected decline of yellow pages of 37%  Competitors had it at 7%  Later projections pegged it closer to 35%

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