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What is Ad Testing?
Why Use Ad Testing?
Is Ad Testing Right for You?
Case Study

 

What is Ad Testing?
Advertisement testing can involve one of several techniques with different purposes.  The process involves presentation of creative advertising materials to individuals within a target market to determine the impact of the ad.

While there are a variety of techniques, one of the most recent and highly effective methods involves the use of the Internet.  Through this medium, a very realistic presentation of creative materials can be presented for evaluation by a variety of markets.

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Why Use Ad Testing?

Ø      Get the most out of your ad dollars Launching a multimedia advertising campaign is costly.  Getting feedback from the target market prior to launching an ad can help ensure success.

Ø      Focus the message – Test a variety of messages to see which are most appealing to your target market.

Ø      Weigh your optionsLet your customers, targets and key stakeholders provide valuable input.

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Is Ad Testing Right for You?
Ad testing is a cost effective technique if you are launching an ad campaign that involves high dollars.  It is an outstanding technique to combine with DesignChek when you are trying to evaluate multiple options or build consensus with an organization.

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Case Study
A large consumer products manufacturing company had commissioned its ad agency to develop several radio spots for a new product introduction.  Prior to launching one of the spots, NMM conducted a quick Internet-based survey with potential product buyers to assess the various ads.  The consumers helped shape the ad campaign as the number one radio spot chosen in the survey ran for an extended period.

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Customer Satisfaction

Due Diligence

New Product Development

Online Surveys

Patient Satisfaction Tracking

Price Sensitivity

Product Placement

Shareholder Surveys

Telephone Field Operations

Transaction-Based Satisfaction Tracking


Understanding the Numbers
"There's no shortage in numbers.  We're awash in them.  We're drowning in them.  We don't need more data.  We need information we can use."  If you have heard comments like this, our quantitative team can help.