As an organization, Chitika has wholeheartedly invested in building out the Chitika Insights research program through staffing, rigorous process management, and a quality data infrastructure. Additionally, our reports rely on our vast trove of ad impression data and our knowledgeable and skilled team of data scientists. It’s this impression-level data and attention to statistical detail that has ultimately led our research to be cited by The New York Times, Wall Street Journal, CNN, Bloomberg, and many others.
Especially in today’s more fluid technology space, sales figures or estimates, while seemingly concrete, actually tell an incomplete story. Company-supplied statistics vary in exactly what they may be reporting, namely:
- Some companies provide unit sales based on what they’ve passed along to retailers (e.g. units shipped), while others report only on units that have actually been sold to consumers (e.g. units sold)
- Others may provide larger sector sales figures, without breaking this down on a product-by-product basis (e.g. Total Hardware Sales)
- A given company may or may not break down sales by geography, and those that do can choose to segment however they wish – by country, continent, or region (e.g. EMEA)
These variances on a company-to-company level make direct comparisons difficult, often requiring additional estimates and guesswork. This is an area where analyst firms add value by harvesting alternative data sources from suppliers and retailers, among other partners. However, the impact of this extra information on the final reported sales estimates is subject to the preferences of the individual analyst or analysts.
What usage statistics, like those provided Chitika Insights, provide is a kind of counterpoint to these valuable, but admittedly subjective estimates and challenging to decipher sales figures.
Of course, while usage-based statistics are a terrific tool, they possess caveats of their own and benefit from the context of other data sources to maximize their value. While Chitika Insights reports on Web activity across the more than 350,000 sites that run Chitika ad code – a decidedly large and varied sample by website size and vertical focus – we can only observe what is happening on the ad network itself. But in terms of observational data sources, the hundreds of millions of impressions we catalog each day may be considered more neutral than data from programs with self-selected user or survey groups, which are often much smaller and may be influenced by self-selection bias on the part of the respondents or participants.
In the case of Chitika Insights, these studies show how users of devices and platforms browse the Web in an unfettered environment – in a much quicker turnaround time than traditional analysts are able to operate. Reporters like Charles Arthur of the Guardian and Greg Sterling of Marketing Land have been on the front lines getting the most out of these varied data sources by contextualizing usage data alongside analyst research, helping to reach conclusions beyond what any individual source could provide.
What reporters and industry watchers are increasingly understanding is that impression-level data provides a previously unseen, on-the-ground view of user activity. When paired with sales figures or estimates, the subsequent combination acts as an even more comprehensive barometer of the overall market.
We’re excited to be part of this new movement.
See our data in action…
- New York Times – September 8, 2014
- Bloomberg – September 22, 2014
- Wall Street Journal – September 8, 2014
- Washington Post – September 22, 2014