DAGMAR marketing model

As discussed in The funnel of marketing, Theory helps but marketing is practical when it comes to business.

You tactics must deliver else you lose the job.

Hence, Refinement with metric driven approach towards marketing was needed. DAGMAR is exactly that. Metric driven marketing where better you analyse data, optimum will be your conversion.

Defining Advertising Goals for Measured Advertising Results.

As per funnel theory, Awareness < Consideration < Conversion

DAGMAR refines consideration into 2 steps:





Comprehension makes the data which helps consumer in understanding the attributes and the features of the product and what the product will do for the consumer.

Conviction is giving assurance to the customer, you're the best choice.

Practical Marketing

  • Define your marketing campaign in these order:
  • Objectives: What do you want to achieve.
  • Who you want to target: Target audience
  • Where they hang out: Channel list

Test campaign to set benchmarks for the campaign ahead. You base your measurement on this metric.

Defining budget, Cost per acquisition, CPC, target audience are necessary before launching a campaign.

This model is what happens across all MNCs and start-ups. You define these and get approvals from your senior for the budget and ace the market.

This model gives you high quality data which can further be used as a feedback loop to keep refining the audience. It is this reason why all marketing campaigns are time driven as market saturates.

No one wants to see same thing on a repeat. Campaigns lose its charm over due course of time. How long?

Till the time you're performing above metrics you have defined, then it is always recommended to keep going. When campaign goes below metrics defined, campaign has run it course and it is time to reflect and use the learnings for more awesome campaigns.

Due to reasons above, successful campaigns are hardly shared until they are saturated in market. Magician never reveals its secret.

Forming community around marketing much alive programming is tough due to reasons above as well.