Brian Clifton (PhD) is a measurement strategist, advisor and renowned practitioner of performance optimization using Google Analytics. He is also the author of Successful Analytics. Hear his thoughts on how to adopt company-wide analytics initiatives, how he’s seen the industry evolve over the years, and his perspective on hiring talent and finding good analytics partners.
Key Learnings:
1. Executives will go to their accountants with detailed questions about where they’re making money or where efficiency can be improved, but those types of questions don’t get asked about web analytics very often, and they should be.
2. Attribution modeling and segmentation are key tactics to employ in order to convince senior-level employees of the importance and usefulness of analytics.
3. Data quality errors lead to a lack of trust in the data and perpetuates the cycle of underutilizing analytics.
4. Organizations ideally need a five-man analytics department to cover all of the necessary skill sets for a well-rounded perspective. But that is way too big of an overhead for most companies. Therefore, partnering with an authorized consultant, e.g. a GACP, is key. The best approach is a hybrid–your internal staff working with your partner.
5. You should treat your analytics partner in the same way you treat your accountants. You work internally to do a lot of the heavy lifting on your finances, but ultimately you go to an independent accounting company at tax time to get the exact figures that you need.
6. There is currently an industry-wide need for more formal qualifications, like in-depth college courses.
7. These days, products launch from Google and Silicon Valley, and then they’re rolled out more globally instead of being pitched to specific markets. Therefore, there is surprisingly very little difference between Europe and North America in terms of how tools are used or how analysis is conducted.
8. Building an environment of continuous education and learning is what’s going to help grow and mature your team, more so than just pay scales.
Interview:
AS: This is Amin Shawki with InfoTrust, and today we’re speaking with Brian Clifton, renowned author, speaker and analytics guru. Brian, thanks so much for joining.
BC: Thank you for having me.
AS: To start, how would you introduce yourself to someone outside the analytics industry?
BC: There are so many different roles in our industry; almost everyone has their own unique job title. It’s very difficult to define yourself outside of saying, “Oh, I work in digital/websites/etc.” I face this predicament all the time, especially when talking to senior executives who don’t know data in-depth like we do. It’s hard to explain what I do without making their eyes glaze over. But I usually say that I essentially work in digital analytics. What that means at a high level is that I analyze digital footprints; in other words, where visitors go to on your website. I try to understand who left those footprints and what their experiences were on your website. The goal is to understand the user base and therefore understand how to get more visitors to convert into customers.
AS: So, you’ve certainly spoken on this topic before, and you’ve written numerous blog posts. You even wrote a book last year called Successful Analytics, which goes into how to deploy measurement strategies with organizations using Google Analytics. What inspired you to write this book and take this career path?
BC: My desire really stemmed from the frustration of getting digital analytics into organizations at a senior level. There are about 30 million websites using Google Analytics now, so the adoptions have been fantastic. But what I often come across is that organizations are looking at very basic numbers: how many people came to the website, how many left, and where they came from. Executives will go to their accountants with detailed questions about where they’re making money or where efficiency can be improved, but those types of questions don’t get asked about web analytics very often, and they should be. I’ve found that there is a lack of trust in the data. Senior management doesn’t trust web analytics data; they trust their accountants; they trust their business intelligence team and they trust their customer analytics team. So, my desire to make sure that web analytics is taken seriously was really what drove me to write all of the books that I’ve written, including Successful Analytics. This books encourages senior-level people to turn analytics into a proper business intelligence tool vs. a superficial visitor counting engine. It does take time and effort to make sure that the data is accurate and to have full confidence in it; but once you get there, the potential is enormous. If you move the needle of your conversion rate by just 1%, that could be millions of dollars gained or saved.
AS: A follow-up question to that point: As far as getting organizations to adopt analytics or understand data quality, how would you try and convince senior management of the value of going beyond the high-level numbers?
BC: There are two important techniques here. First, you have to make sure that all your marketing campaigns are tracked correctly. That’s just called “campaign tracking” in Google Analytics terminology. Many senior managers are well aware of attribution and the issue of attribution modeling. For example, say that someone comes to your website many times from different touch points (social, organic search, paid search, etc.) Perhaps they convert after five or six visits. But what step in the process gets credit for that conversion? It could be the first click or the last click or a certain message on the page. This opens up a complicated subject called attribution modeling. For it to work, you have to make sure you’re tracking all your campaigns properly so your analyst can properly analyze the data. It’s easy enough to explain, but the modeling part is much harder; you have to have those fundamental building blocks.
The second technique is segmentation. It’s so important to be able to separate out customers vs. prospects vs. staff, etc., and to also be able to segment your customers into high-valued vs. lower-valued groups. It’s quite easy to do this if you measure the performance of the campaign by looking at the percentage of all your traffic as a denominator of the performance. Maybe you’ll realize that half of your traffic is existing customers and is therefore not relevant to the campaign, which then makes it easy to show that the performance in that campaign is twice as good as you actually think because your target audience is half as big. Senior managers are already thinking about segmentation and attribution like this, so these are two big techniques to use to convince them to take the data a lot more seriously and invest in the time and the effort to do it right.
AS: Shifting gears a little bit; so, you were the first head of web analytics at Google Europe about ten years ago. Since you’ve been around analytics so long, how have you seen the industry evolve and change, for better or for worse? You’ve already touched on how analytics used to be just counting visits in and out, etc. Is that still the case, or do you actually see organizations taking that deeper look and doing segmentation?
BC: I’ve been working in this field for almost 20 years now. I joined Google in 2005, which was a very exciting time to be a part of launching the product and to help build the expertise in Europe. Obviously, there has been a huge shift in terms of adoption. In those early days of Google, it was estimated that about 30,000 people were using analytics. Now, ten years later, it’s 30 million; a 1000-fold increase. Now, almost everyone who launches a commercial website uses Google Analytics, partly because it’s free and partly because it’s easy to do. It’s definitely not a niche industry anymore. And the available analytics tools have certainly gotten a lot more sophisticated. The tools no longer just count how many people come to your website anymore; they help segment those people. It’s more about understanding the quality of traffic and being able to focus on the high-value customers.
In terms of negative changes, I do think that analysis remains quite stagnant. There are a few innovative companies out there doing some really sophisticated stuff, but not many. If you think about the adoption of 30 million, the numbers of companies that have actually invested in their understanding and use of their web analytics data, as oppose to just counting visits and pageviews, is next to nothing. A lot of companies invest in their own customer analysis, but very few look at the much wider picture of the web. I am also disappointed that I keep seeing the same basic errors being made in the analysis process, particularly when it comes to data quality, because bad or unknown data leads to a lack of trust in the data and perpetuates the cycle. (You can take part in my ongoing research on trust and analytics here.)
AS: You recently gave your predictions on the biggest trends for 2016, and you mentioned that finding quality talent is always a challenge. In light of the pervasive lack of investment in data quality that you mentioned, do you have any recommendations on how to build analytics capability with an organization so they can be more innovative and use data more frequently?
BC: Having good analysts with the right skill set is absolutely key. I think scientists are really well-suited for digital analytics. I come from a science background, so I might be biased, but people with a scientific background who understand data, statistics and confidence intervals would be perfect for this type of role. I think a lot of people like scientists, economists, and possibly even philosophers don’t actually realize that there is a whole industry in digital marketing that is really well set up for them.
Most companies ideally need a team of five or so people in their analytics department to cover all of the necessary skill sets for a well-rounded perspective. You need people who can maintain good data quality; do attribution modeling; execute marketing; provide a great user experience, etc. Organizations ideally need a five-man analytics department to cover all of the necessary skill sets for a well-rounded perspective. But that is way too big of an overhead for most companies. Therefore, partnering with an authorized consultant, e.g. a GACP, is key. The best fit is actually somewhere in between where you invest some resources in both internal expertise along with an outside partner to help advise you. A lot of companies think they have to do it all in-house and really struggle. And on the other hand, there are other companies that isolate their data by outsourcing it completely. You don’t want to silo things in that way; you really want the best of both worlds by hiring some internal staff and a partner that can bring that extra expertise and experience.
AS: I’m curious on your thought here about partners. Many organizations have partners that run their media and marketing campaigns. Do you think these types of partners are the right fit for organizations to work with from an analytics perspective? Could marketers also become great analysts?
BC: No, I don’t think they’re a good fit; you need an independent data partner rather than somebody that’s also looking at your advertisement budgets. It’s just like how companies have independent auditors like accountants. You work internally to do a lot of the heavy lifting on your finances, but ultimately you go to an independent accounting company at tax time to get the exact figures that you need. I treat analytics in the same way because data is so valuable to organizations if used correctly. So, when you partner, it’s important to make sure that the people that look after your data are experts in data, and you often just don’t get that with media agencies. They are looking at branding and reach, etc. Being independent with your data is a much stronger approach to take.
AS: Very helpful, thanks! To shift gears slightly, I noticed that you speak a lot at university courses and conferences like ours this past year, “Analytics That Excite.” What are the most common questions or struggles people share with you at these speaking engagements?
BC: Most of the questions tend to be from people wanting to learn more. I’m finding that people want to study full time and pursue analytics as a career. So, I see a lot of enthusiasm about it, which is always fantastic to see. But I think that the types of questions that I get really make me feel that there is an industry-wide need for more formal qualifications. So, I’d love to see a one-year, in-depth college course, for example. People who are new to this industry tend to know small snippets of certain aspects of analytics. They might focus on attribution modeling or campaign tracking, but seeing how all of these pieces fit together is quite difficult to do when you take this one conference or one workshop approach. And so I really think that a more formal, structured approach to the subject would be great.
AS: Along similar lines, you speak at lots of different global universities and conferences. Do you see any differences in adoption of data analytics or enthusiasm across different regions of the world like Europe vs. Asia or the Americas?
BC: My experiences have been mainly throughout Europe and North America and a little bit in Asia. And yes, you would expect to see differences. I’m English, and there was always a saying in the UK that we were three or four years behind the US in terms of technology. That was always kind of the joke, but I actually don’t see that anymore. Products launch from Google and Silicon Valley, and then they’re rolled out more globally instead of being pitched to specific markets. And so, I see surprisingly very little difference between Europe and North America in terms of how tools are used or how analysis is conducted. I live and work in Sweden now, and the difficulties, challenges and opportunities of the Nordic countries are almost identical to those in the parts of Europe that I worked. Same with the UK vs. clients I’ve worked with in the US.
AS: Very interesting; great to get your perspective! Final question here: do you have any closing thoughts or key takeaways for aspiring analysts or organizations that want to be more data-driven?
BC: I think one thing I’ve learned is that even very experienced and knowledgeable analysts still have a thirst for learning, no matter how senior they become in an organization. So, when you’re trying to build a team within an organization, you need to keep that need for knowledge at the heart of the team and use it in creative ways. Go to conferences, buy books, have a book club where you talk about your industry. There are quite a lot of books out there now on the subject. Building an environment of continuous education and learning is what’s going to help grow and mature your team, more so than just pay scales.
