Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Scrubbing the Data: A Brand Housekeeping Guide


Published on

Data may be the fuel driving the digital targeting revolution, but much of what fills brands’ tanks is poorly filtered, stale, low-octane. From naming conventions to well-aligned KPIs, consistency of data over time to recency of behaviors – there are many forms of data dirt. 3DayBlinds’ Dan Williams recounts his effort to increase the digital ad engine’s effectiveness by starting at the fuel line.

Published in: Marketing
  • Be the first to comment

  • Be the first to like this

Scrubbing the Data: A Brand Housekeeping Guide

  1. 1. Scrubbing the Data: A Brand Housekeeping Guide
  2. 2. • 40 year old custom window treatment manufacturer and direct to consumer retailer • Provide design, measurement, manufacturing, support & installation of custom window treatments • In-home model only, at one point had 200 retail locations
  3. 3. Define The Thing What is “clean data” YOY?
  4. 4. 64% of all statistics are wrong 32% of the time • Transaction ID • Trans ID • TXID • TransID • Transid • Transaction
  5. 5. Let’s talk about all important KPI’s • Are you looking at the right numbers? • Product X returns are higher than expected? • Compared to what? • Over what period of time?
  6. 6. A Real Quote About Real Stuff • The Experian Data Quality Report indicates that inaccurate data impacts the bottom line of 88% of businesses, with the average company losing 12% of its revenue as a direct result.
  7. 7. Type of Data Issues • Allocations • Media Channels • Social? • Digital? • Retargeting vs Prospecting • Case sensitivity / Misspellings / Culture / International • Funnel Categorization • Lead qualifications • What is a customer? • Home? • Individual?
  8. 8. Pay Attention • Educate EVERYONE • Change Habits TODAY • Be disciplined • Make it repeatable • Quality standards MUST BE documented • Review and AUDIT your data • Invest in tools that check for human error • Everyone has to get better always
  9. 9. What is next? Your mind is a categorization machine, busy all the time taking in voluminous amounts of messy data and then simplifying and structuring it so that you can make sense of the world. This is one of the mind’s most important capabilities; it’s incredibly valuable to be able to tell at a glance whether something is a snake or a stick. For a categorization to have value, two things must be true: First, it must be valid. You can’t just arbitrarily divide a homogeneous group. As Plato put it, valid categories “carve nature at its joints”—as with snakes and sticks. Second, it must be useful. The categories must behave differently in some way you care about. It’s useful to differentiate snakes from sticks, because that will help you survive a walk in the woods.