Himanshu Sharma is the founder of Optimize Smart (formerly SEO Takeaways). He runs one of the world’s most popular blogs on analytics on optimizesmart.com. Himanshu is also the author of three books about web analytics, conversion optimization, and attribution modeling.
I recently had the opportunity to talk with Himanshu about digital analytics including misconceptions about working with data, what it means to be data-smart, and mentorship. Our conversation is below:
If you’re on a plane and you have to introduce yourself, what do you say?
“I help online businesses in finding and fixing their tracking and sales issues.”
If someone is interested then he/she can ask follow up questions like ‘what type of sales issues’ or ‘what type of tracking issues,’ etc. If not, then at least they get some idea of what I am talking about. I don’t use industry jargons.
What inspired you to pursue a career path in digital analytics? You are one of the most well-known contributors and experts in digital analytics. What do you feel was the tipping point of how you decided to go in this direction?
I started my career in digital marketing (SEO, PPC etc) and you can’t manage/optimize marketing campaigns without sound knowledge of analytics. So I have been using web analytics from day 1 of my career in some form or the other. But at that time, I never thought of becoming a full-time analyst.
Then one day, back in 2012, I got an email invite from ‘Market Motive’ to take their web analytics master course and get the chance to be directly coached by ‘Avinash Kaushik’. I jumped at the opportunity even when the course fees was over $3k and I had never enrolled in a course so expensive before.
It was a three months training program in which there will live online classes, assessments, projects etc. It was a tough course to pass as I was directly assessed by Avinash and it was really hard to live up to his expectations especially at that stage of my career when I was comparatively a novice. He, in fact, did not pass me the first time because I made some stupid maths and stats mistakes while analyzing and presenting the data (and which later prompted me to write an entire book on maths and stats behind web analytics, so that other people don’t repeat the same mistakes).
But the training was really an eye opener for me. Before taking the course, I was a ‘know it all and nothing else left to learn’ guy. After taking the course, I realized, how little I knew. This course brought a turning point in my career and I decided to focus mainly on analytics.
What do you think are the biggest misconceptions about working with data?
That the reported data is accurate and it somehow provides complete; absolute insight. That nothing exists outside the digital realm and if something can not be measured then it should be discounted from the analysis. That technology and tools are panaceas which can somehow make up for operational inefficiencies, lack of expertise and solve all the problems around ROI.
What do you think separates exceptional companies from everyone else? By exceptional, I mean exceptional in their use of analytics.
It is the data-driven work culture which values analytics and testing. If your company does not value data and treat web analytics as some sort of side project, then you may have a hard time getting all the required tools and resources for your work.
What are three to five key KPI’s or metrics that you consider to be the most important for marketing, from your experience?
Three top KPIs: ‘Return on Ad Spend’, ‘Raw Sales volume’, ‘Cost Per Acquisition’.
Let’s talk about your book, Maths and Stats for Web Analytics and Conversion Optimization. There’s one chapter in the book that I think many readers will find surprising; you write that you should stop optimizing for conversion rate. Why?
Because conversion rate has a weak positive correlation with sales and zero correlation with cost. Conversion rate has absolutely no impact on optimizing cost. You may have a very high conversion rate but if your cost per acquisitions is also very high, it will kill your profit and ROI.
The two metrics that actually drive sales are ‘average order value’ and ‘number of orders’. Conversion rate has a weak positive correlation with sales because it does not take into account ‘average order value’ in its calculation and also because it is a ratio metric, where the ever-increasing traffic on your website will always tend to lower your conversion rate. So decline in conversion rate is not always a bad thing. Similarly, increase in conversion rate is not always a good thing. Your conversion rate may have increased because of decline in website traffic.
Other than that, your reported ‘conversion rate’ may have got ‘statistical significance’ and data interpretation issues. So it is not really the best metric to focus on.
The book concludes that you should move your organization from ‘data-driven’ to ‘data smart’. Can you explain the difference and why it’s so important?
‘Data-driven’ means you are just blindly following the data. You are not taking context, business know-how and day to day business operations into account. You are dismissing everything which can not be backed up by data. Data smart means you look beyond data and take business and marketing decisions based on context, faith and day to day business operations. Data smart means you understand what your KPIs can do and can’t do and where to trade off.
You’ve also written books on attribution modeling and email marketing analytics. What drives your choice of topics for books?
I wrote a book on attribution modeling because there was none. Regarding email marketing analytics, it was a fun little project. Besides, I like sharing my knowledge and expertise.
Can you give us a preview of what you’re working on in the next 6-12 months? Do you see yourself writing another book?
I am working on the second edition of my maths and stats book. But I am not sure how long it is going to take. I will be adding more study material to my web analytics training course.
You’ve been in a space of digital analytics for over a decade. What do you think are some of the biggest changes? What things are you most excited or skeptical about?
I love all the big and small changes Google makes to its products. Whether it is Google Analytics, Google Tag Manager, Google Adwords or Google data studio. I am excited about getting the free version of the Google attribution tool.
If you were to give advice to yourself when you were just getting started in the space of analytics, what would it be?
I wouldn’t have given myself any particular advice as such. Fortunately, I had a very good start and a solid foundation from the very beginning. However, if you are just starting out in analytics, take a crash course from an expert, seriously. Like I did. Don’t waste your time learning things the hard way, on the job, through hit and trial. This is an incredibly slow way to learn ‘world-class web analytics’.
Sure, all the information that you would possibly need is available online for free if you dig really deep. Sure you can learn from conferences and webinars. But the knowledge you get will always be fragmented. There is no structure to it. No one will teach from A to Z and on top of that, you don’t know whether it is beneficial or not. The Internet is also choke-full of misleading/incorrect information.
It would take you years or even a decade to learn all those things by yourself which you can learn from an expert, in a couple of months. This is the power of mentorship. Find a mentor and learn all the best tips and tricks of the trade. Why repeat the same mistakes which others have made before you. Learn from other people’s mistakes and make your own original mistakes. That’s how you grow fast.
Optimize Smart has recently launched an 8-week, online course on web analytics. Check it out here!