Andy Beal Interview: More Detail About Blog Monitoring with Trackur

by Steve Broback on April 29, 2008

I had a chance to interview Web marketing guru Andy Beal recently about Trackur, his new blog/press monitoring service. Since we had recently unveiled our own sentiment tracking system, I was intrigued by what appears to be a complimentary offering.

I tried to get Andy to reveal a little of what goes on behind the technological curtain, but understandably he was a bit reserved about detailing trade secrets.

Note the final paragraph. This is where Andy really aligned with our thinking regarding sentiment tracking. As Alan Wilensky says, sentiment is the weakest of CGM metrics.

I’d be eager to hear from any clients how the service is helping them in their brand monitoring efforts. The current buzz has been quite positive.

Here is the interview in it’s entirety:

Steve Broback: Many companies have “rolled their own” monitoring systems by aggregating custom search feeds from multiple sources. Other than the time it takes to create these searches, the challenge is that duplicate content, old content, and spam (splogs!) need to continually be weeded out. Is Trackur intended to be the alternative to this largely manual process?

Andy Beal: Absolutely! We built Trackur because creating custom search feeds was too time consuming and we couldn’t get the filtering and reporting options we needed. With Trackur, you enter your keyword one time and then let Trackur automatically monitor the different types of social media for you. You can filter out unwanted items, sort the results, email to co-workers and subscribe via RSS or email updates. You can’t do any of that when you manually monitor your reputation.

Steve Broback: Are we correct in assuming that Trackur taps into multiple existing search engines and then de-dupes and de-spams the results?

Andy Beal: Trackur does a great job of filtering out the noise and focusing on the signal–the content that matters most to your reputation. It doesn’t remove all duplication and actually, you probably don’t want to remove it all. A post might show up in Technorati one week, then again on the next–if you removed the duplicates, you’d miss this reoccurrence.

Steve Broback: What search engines are you leveraging?

Andy Beal: Trackur pulls from a wide selection of content. It’s not really a search engine, more of a reputation aggregator. We don’t provide a complete list of sources, but we do include some unique content such as Flickr, YouTube, and Digg.

Steve Broback: Have you created your own crawler of any kind, or is it exclusively tapping into existing indexing services?

Andy Beal: We didn’t set out to make Trackur a web crawler. It’s a reputation monitoring and aggregation tool. It’s power comes from bringing a wide range of web content together in a central database, then giving you powerful tools to manage the data.

Steve Broback: Google has been working this problem for years without much luck — how good is Trackur at removing splogs from results?

Andy Beal: Removing splogs from search engine results is extremely tough, so we’ll leave that to Google’s immense resources. Instead, Trackur focuses on providing clients with the tools they need to pinpoint conversations which include their reputation. If a Trackur client finds a splog showing up, they can add a filter to remove it from any future results.

Steve Broback: How do you avoid filtering out relevant content?

Andy Beal: We advise Trackur users to start off with the broadest of searches. For example, if you are Apple, start by monitoring “Apple” and see what’s tracked. If you find too many irrelevant results–or simply want to be more refined with your monitoring–you can add filters to focus on a particular word (such as “iPhone”) or remove the unnecessary results.

Steve Broback: How do you insure that old posts don’t re-emerge in search results?

Andy Beal: Actually, we don’t believe it’s a smart practice to say, “never show me this result again” when it comes to reputation monitoring. If a blog post attacks your reputation, you need to know if it keeps resurfacing–that would suggest that the post is being revisited or discussed by others.

Steve Broback: Have you applied for any patents specific to Trackur?

Andy Beal: Not at this time. There are processes we could patent, but we’re not finished enhancing Trackur’s technology, so we’ll probably wait until we’ve added new features, before applying for a patent.

Steve Broback: Shane Atchison says sentiment is the “next great analytics frontier”, and we’ve been focused on that metric of late. Are there any plans to integrate sentiment tagging into Trackur results?

Andy Beal: Sentiment analysis is definitely something we exploring with Trackur. The biggest problem is that it’s virtually impossible to accurately ascertain the sentiment of web content using an algorithm. Apart from the need for human interpretation as to what is positive or negative, technology gets confused by statements such as “Apple Mac’s are wicked bad!”

{ 2 comments… read them below or add one }

1 Andy Beal 04.30.08 at 5:51 am

Thanks for the great questions Steve! I hope your readers will take our 14 day free trial and give Trackur a test drive. :smile:

2 Joseph Fiore 05.09.08 at 5:49 am

Hi Steve,

As a stakeholder in the ORM space and a firm believer in delivering value to our clients, I was intrigued by your statement about sentiment being the weakest metric. I am curious as to how you have you arrived at this conclusion? If we are speaking about the debate between machine vs human analysis, then it might be more accurate to state that machine automatation and analysis is limited in interpreting such things as tonality, context and/or risk.

I’m of the opinion that sentiment metrics are one of the key ingredients in properly metering out the evolution of online reputation monitoring, and due to the limitations of machine analysis, human analysis is the only chance we have of evolving to the stage where we can accurately filter nuissance content (see my blog comment), and to arrive at any semblance of interpreting risk and context, each at different stages of reputation management.

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