What would you like to ask Avinash Kaushik?

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boxer The gloves will be tied tight. Brightly colored silk dressing gowns will be shrugged to the floor; gum-shields inserted. In the blue corner: yours truly. In the red (and blue, yellow and green) corner, web analytics heavyweight, Avinash Kaushik. As the crowd bays for blood, battle will be joined. The Garden never saw anything like this.

Well, ok, it’ll probably be a bit more civilized (well, a lot more civilized) than that. But at next week’s E-metrics Summit in San Jose, Avinash and I will indeed be going head to head in the “Rules for Analytics Revolutionaries” session on Wednesday May 6 at 3.25. In that session, I’ll be asking Avinash some genuinely tricky questions to really get to the heart of some of the thorniest issues around web analytics today, such as campaign attribution, free versus paid tools, and what, really, the point of all this electronic navel-gazing really is.

But I could use your help. In my comments box below, or via e-mail, suggest the question(s) you’d most like me to ask Avinash next week. This is your big chance to ask Avinash the question you’re too embarrassed/polite/nervous to ask him in person. If you’re going to be at the Summit, then be sure to come to the session to see if your question gets asked; if not, I’ll post a follow-up post here after the event and shall be sure to include Avinash’s answers to any questions from the blog.

So come on – what have you got to lose? It’s not like it’s you who’s going to be picking a fight with one of the industry’s most revered and respected advocates, is it? Leave that to old numb-knuckles here.

6 thoughts on “What would you like to ask Avinash Kaushik?”

  1. For some time now I have been trying to figure out the best way to track conversion attribution. I am starting to see trends that companies are using attention driving activities in order to create “intention” to search (or better spread the love via social media).
    Seth Godin recently put it much more eloquently that we should expect to see this in future marketing campaigns;
    http://bit.ly/BfSC1
    A great example of this is the buzz Adidas created with the “impossible is nothing” campaign. Type in impossible is nothing and see who appears at the top of Google then look at all the other results from fans of the advert. According to Google Trends we worked out they were getting at least 135,000 searches a month for that term or a combination of it.
    I have started monitoring this activity via a combination of Google trends and tools like Blogscope & Twitalyzer and have had some success measuring lift over campaign life-cycles but I feel it can be done better than my initial testing. So to my question…
    How/what would you use to best measure campaign attribution to conversion from attention driving marketing to intention/social medias that come as a result? What would be your advice on how best to do this?

  2. When analysing customer conversion rates it is common to segment your traffic by referring source. For example, to calculate the ROI on PPC, or measure the value of partnerships, other referring sites, organic search etc.
    That said, sales may not (and in some business models are unlikely to) occur on first visit. On average, a user may visit 5, 10 or 100 times before they convert. If this is the case, what is the best way of attributing that sale to a referring source of traffic? Would you suggest the first source, for example if a user came in via PPC, then subsequently as direct traffic? What if a user has a diverse usage profile, sometimes arriving by PPC, sometimes via organic search and sometimes directly – take the most frequent referring source, or something else?
    I would be interested to know whether Avinash has addressed problems such as these in the past, and if so how.

  3. Recently we have seen that Twitter integration into different web analytics tools has been picking up. I would like to know whats his(Avinash Kaushik) view on whether we can see more integration of other popular tools/services like Facebook, Digg, stumbleupon, reditt, etc will come up. I’m curious how customizable, segmented and user friendly web analytic tool’s can we see in the near future?

  4. Hi Ian,
    I’d like to know how B2B marketers can overcome the curse of small sample sizes in data.
    Cheers,
    -Alex

  5. I have wondered how to measure press releases in your analytics? If you send press releases out through something like PRNewswire, which sends it to 1,000s of sites, how can you aggregate all of the sources to see the impact on your site?
    Each individual website might only send a few visitors, so the referral report doesn’t help too much.
    thanks,
    Scott Petrovic

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