Digging through big data is a bit like cleaning out your closet – you often find gems that you either had forgotten about or you didn’t even know you had.
Finding the full picture in that heap of data and multiple storage silos is the focus of our webcast with Benjamin Spiegel (@nxfxcom), director of search operations at Catalyst, Wednesday, July 17th at 11 a.m. Eastern.
In the webcast, “Combining Paid & Organic, Social & Earned Media Data to Drive Deeper Insights with Spotfire,” Spiegel shows you how getting all of this data organized by category can drive insights for your organization.
He’ll examine how taking a simple key phrase strategy, using the right targeted keywords online and integrating all the data from your different silos can give you an organized strategy for concrete paid, organic and content campaigns.
In preparation for the webcast, we thought it would be fun to take a look at how setting up your search strategy compares to cleaning out your closet. Let’s get started.
Both cleaning closets and wading through search data can be overwhelming.
You have to wade through a lot of “stuff” to get to the goods and that applies in both cases. Spiegel recently spoke about this in his talk, “Driving Search with Big Data,” at Interactive Digital 2013.
In his presentation, he explains the steps for breaking down the data during the API process.
To get started, you need to create your category criteria.
In the case of cleaning up your big data, it starts with translating the business needs into KPIs (key performance indicators) and then determining the data sources.
Build connectors (or your catchalls for all that data).
This allows you to get the raw data into the right buckets. It’s much like the keep, donate, sell bins you use in a real closet overhaul.
Determine where the “keep” data will be stored before you analyze it.
In this step, you’ll select your storage and aggregation method to manipulate and prep the data for visualization and analyzing.
Think of it as putting pants with pants, summer with summer, etc., in the closet analogy.
Visualize and explore with filters and segments.
Once you’ve sorted the data into its final storage “home,” you can use filters and segments to analyze and really “use” the data.
A good comparison is taking the pieces in your closet and creating a “look book” of the outfits and options your wardrobe offers.
Here’s a quick look at how this plays out with a keyword strategy.
One company wanted its search strategy to connect with 50% of consumers searching in its particular market. Before the “closet cleaning,” the brand was only reaching about 15% of searchers.
Here’s how the company sorted it all out:
- Took the top 20 rankings for approximately 4,000 key phrases
- Collected audience data for all the key phrases from three commercial sources
- Did a sentiment analysis on all the discovered URLs
- Analyzed and organized the inbound links by traffic, quality and authority – that left the company with 63 data points per domain
- Did some filtering of the URLs based on the link authority, audience alignment and engagement rates for the data points
- Discovered about 170 sites for targeting and engagement
- The final result was a tailored strategy that got the brand mentioned in 60% of all the search results – exceeding its goal by 10%.
- Subscribe to our blog to stay up to date on the latest insights and trends in big data and big data analytics.
- Please join us on Wednesday, July 17th at 11 a.m. EDT for our complimentary webcast, “Combining Paid & Organic, Social & Earned Media Data to Drive Deeper Insights with Spotfire,” presented by Benjamin Spiegel, Director of Search Operations, Catalyst and Ben McGraw, Director of Industry Solutions, TIBCO Spotfire. In this webcast, Spiegel will explore a variety of search data and demonstrate how Spotfire can be used to build illustrative dashboards, drive insights, and refine paid and organic recommendations for more effective content strategies.
Spotfire Blogging Team