Win at Web Analytics: Top 7 Ways to Influence Your HiPPO

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Welcome to the first in my series of posts to help web analysts ‘Win at Web Analytics!’ These upcoming series of posts are designed to reveal some useful web analytics insights, and teach some great foundations that you can apply to any type of web analytics work.

This first ‘Win at Web Analytics’ post discusses HiPPOs. Not the animal that wallows in dirty water – but a different kind of animal found in the workplace. A HiPPO is the ‘Highest Paid Person’s Opinion’ if you believe Avinash Kaushik’s original definition , or ‘Highest Paid Person in Organization’, if you believe Eric Peterson newer interpretation.

But why do you need to influence your HiPPO, you may ask. Well, they can often be a major obstacle to web analysts and overrule their findings. HiPPO’s beliefs are often wrong, thinking that they know the customer need’s the best. They are particularly problematic when they are responsible for many other departments, not just web analytics (believe me, I have met my fair share!) Here is how you can try and influence your HiPPO…

The Influence Basics – Read these First:

1: Read ‘How to Win Friends and Influence People’. Even though this Dale Carnegie classic is now pretty dated, its still considered to be the grandfather of the ‘influencing’ world. It still has some great wisdom that even applies to the web analytics world.

2: Read ‘Influence – The Psychology of Persuasion’This book by Robert Cialdini is one of the most enlightening business books I have ever read. Pretty soon your HiPPO could be eating out of your hands by using the great principles in this book.

3: Become an Office Politics Expert. To succeed with influencing your HiPPO, you need to be well versed with office politics in general. Here are some great articles and websites that well help you own your way to influencing your HiPPO (and helping your career!):
Play Office Politics Without Getting Dirty
How to Improve Your Skills at Office Politics Daily News

Now Arm Yourself With These Tools to Help Influence Your HiPPO:

4: Analytics Testing Tools. Testing is a great new phenomenon that allows you to prove your web analytics hypotheses and suggestions. Instead of telling the HiPPO that you think your suggestions will work, you can now actually show him results based on your suggestions. If you are on a budget you can easily make use of Google’s Website Optimizer tool (free!) to do multivariate testing (testing more than one thing at once). Or if you have a bigger budget you can try Offermatica. How did we ever survive without these tools?

5: Great Charts and Tables that perfectly visualize what you are trying to convince your HiPPO to do. Remember, a graph is worth a thousand numbers – HiPPOs are very busy and often don’t have time to read and thus become very visual creatures. If you are looking for a great book on creating great graphs and tables, go grab a copy of Stephen Few’s ‘Show Me the Numbers: Designing Tables and Graphs to Enlighten’. It’s an excellent introduction.

6: Benchmarks and Competitive Data. Giving your HiPPO industry standard reports, benchmarks and competitive data can be an enormously powerful weapon to influence your HiPPO with. That way they can see its not just your opinion – that experts and data backs you up.  There are some great websites offering competitive data, which is particularly relevant for dealing with web analyst HiPPOs – and are great examples.

But remember, now you know how you can influence the HiPPO, it doesn’t mean your own opinion is correct or any better. Well, whose opinion matters the most in web analytics? Simple. The customer! And what is the best way to find your customers opinion? Regular clickstream analysis only gets you so far- you need something that leads me to number 6:

7: Web Surveys. These qualitative tools can help you get straight to the horses mouth – the customers opinion, and help see how correct you and your HiPPO’s opinion is. If you are on a budget you can use to run your web survey’s – if not you can use Question Pro or Opinion Lab, which are more expensive, but more versatile solutions. And what questions should you be asking? Heres two big ones – ‘What Was Your Reason for Coming to this Website Today’ and ‘Did You Succeed at This Reason – If Not, Explain Why’. Simple, yet powerful, revealing questions.

And lastly… but not leastly…. don’t forgot to smile! You will be surprised how far this may actually gets you! Try it next time you are talking to your HiPPO – you should be pleasantly surprised when they smile back! 🙂

I’m curious to know what people think of these 7 ways – and if anyone has any other great methods for influencing HiPPOs….

Found this article useful? Please share it on social media. Thanks!

  • Great post Rich. It is always difficult for a HiPPO to argue against two things:

    1) Customer voice (tests, surveys, usability etc).
    2) Relevant comparison external benchmarks.

    No one likes to close their ears to customers and no one likes to look bad in comparison to the competition! : )


  • Hi Rich,
    Great post, keep up the great work! When are you going to be ready to get back to beautiful SD? We miss you. 😉

  • Rich,

    Great article. Love the HiPPO acronym — it’s memorable. Dale Carnegie and Robert Cialdini are two authors I strongly believe in as well and recommend.

    It was a nice surprise to see your reference to our resource site, Thanks!

    Look forward to your future posts on ‘Win at Web Analytics!’

    ~ Franke James, Editor and Founder

  • Great post Rich! You have always been good at the art of persuasion with the HiPPOs. Cant wait till we get to collaborate again soon.

  • Good pointers in this posting. Along with Avinash, the Microsoft Experimentation Platform team also uses the HiPPO term to spread the notion of “data-based decision making”. See the “Practical Guide to Controlled Experiments on the Web” paper at

  • Hi Rich, I have found this article very interesting, and… will starting using the term HiPPO from now on!
    Regards, Doppiafila

  • Hi Rich,
    Good post. I think that it worth adding Hitwise, comscore and event Netcraft to paragraph 6.

    Good stuff.


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  • For nearly a decade, I was a VP at an eight billion dollar a year company, so I was the “HiPPO”.

    I supervised twenty-four analysts, managers, and directors. There were many times when I valued my opinions over data-driven arguments from analysts.

    1 – Unaudited, Flawed Data. The analyst performed work that was simply flawed. The analyst failed to audit results for data accuracy, or had cells in spreadsheets that linked incorrectly, causing the data being presented to simply be incorrect. Once Execs feel like they cannot trust the analysts, Execs go with gut instinct. An analyst can go a long way to gaining credibility by simply making sure that the data being presented is 100% accurate, all of the time. This isn’t hard. If you are measuring conversion rate, and you know that conversion rates on Cyber Monday were 10%, make sure that the conversion rates in your presentation are 10% for Cyber Monday. Easy!

    2 – External Data. Too often, analysts would cite Forrester Research data instead of in-house data. I don’t care that Forrester Research predicts that mobile commerce will be a six trillion dollar industry in 2023, I care about selling something next month. The analyst has greater credibility when using company-specific customer data. Too often, analysts default to cute infographics from research companies, bloggers, or trade journalists. Analysts who use in-house customer data, and make insights/inferences supported by in-house customer data tend to be trusted more by analysts. There’s nothing wrong with external data … but be sure to tie it back to in-house data.

    3 – No Solution or Invalid Solution. I supervised numerous analysts who were able to criticize anything/everything, they’d present data to prove everything wrong about what a company is doing, but couldn’t provide a viable path to the future. Execs, not surprisingly, want a viable path to the future. Analysts can solve this problem by partnering with an Exec, finding a mentor if you will. The analyst can ask questions of this Exec, in order to gain context, this context is used in subsequent presentations with perceived HiPPOs.

    4 – Confidence, not Arrogance. Execs have a sixth sense for detecting confidence. The analyst knows more about analysis than just about anybody else, so be confidence about this … not arrogant, but confident. If the analyst doesn’t know something, simply say “I don’t have the answer to that, sorry.” I can’t tell you how often Execs are disarmed by that sentence.

    5 – Motivation. Execs are compensated differently than analysts are. At the companies I worked at, Execs earned bonuses, often for eighty percent of annual salary. In other words, if an Exec earned $300,000 a year, the Exec could earn an additional $240,000 at the end of the year if certain performance objectives were met. In most cases, company profitability is the biggest component of the bonus payout. So, if you want the Exec to do what you are saying, make sure you are speaking the language of the Exec (profit), and make sure your data leads to increased customer profitability. Link your outcomes to future customer profit, and you’ll have Execs who are much more likely to listen to you.

    6 – Geekspeak. Too often, analysts would tell me the war stories associated with getting data to plug into a simple table in Excel. The Exec isn’t interested as interested in how the data was acquired, the Exec cares far more about what should be done with the data. I realize analysts go through heck to get information and want people to understand what it takes to get to an answer — keep that secret when presenting to an Exec.

    7 – Context. This is a big deal, and analysts aren’t exposed to this often. The analyst presents findings that the Exec wants to implement, but the Exec cannot implement the findings because other Execs in other departments won’t partner with the Exec. So the Exec defaults to a gut-instinct-based decision that is offensive to the analyst, but is more likely to move the needle among Exec peers.

    8 – Not Always Right. I led 24 analysts/managers/directors. If I gave the same problem to 24 people, I’d likely get twelve different solutions and twenty-four different recommendations. Execs understand this. What seems like science to one analyst is opinion to another analyst. Execs have to make judgments about science/opinion, which, to one analyst, seem like a “Highest Paid Person’s Opinion”, but to another analyst, seems perfectly reasonable.


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