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Laura Parfitt, lead, product analytics and data science, Google UK

Laura Parfitt, lead, product analytics and data science, Google UK

How is your organisation using data and analytics to support the corporate vision and purpose?

 

Google’s mission is “to organise the world’s information and make it universally accessible and useful”. Data is fundamental to Google products, and often data is the product. Analytics is being used across all areas at Google to improve products for the end user and, in turn, for Google, too. Google’s cloud gaming platform, Stadia, is using analytics to understand how users are experiencing the platform, whether in terms of the quality of the game stream, user engagement and monetisation, but also how well the platform is serving its partners who develop and publish games with a long term vision to become the game development platform of choice.

 

2020 was a year like no other - how did it impact on your planned activities and what unplanned ones did you have to introduce?

 

One positive trend we saw in Q2 was a huge increase in gaming engagement as people had more time at home. While Stadia had plans to roll out free trial periods, we doubled down on these acquisition efforts to make sure Stadia capitalised on the opportunity.

 

Less positively, we had to cancel plans for DEI events, such as the Women’s Summit I was involved in planning. Lots of similar events and training have been cancelled or postponed indefinitely, where online versions just wouldn’t be effective. We’ve been able to be creative when it comes to team building though, for example, our team Christmas event was an online cook-a-long from a restaurant who provided pre-prepped meals and a wine pairing, so not all was lost!

 

Looking forward to 2021, what are your expectations for data and analytics within your organisation?

 

Stadia launched in November 2019 and analytics is just getting off the ground. 2021 will have a focus on creating best-in-class data infrastructure to set us up for future success. There’s a lot of scope to cover - some areas need setting up with the basics, such as a measurement framework for executive reporting. Other areas are a little more mature, and so the focus this year will be to go deeper on the analysis and to try to understand the causal relationships behind the trends and enable better decision making around the business model and content strategy.

 

Is data for good part of your personal or business agenda for 2021? If so, what form will it take?

 

Google allows employees to take time out each year to spend working for charities of their choice. They also provide a platform to match your skills with volunteering opportunities. A couple of years ago, I signed up to help a data visualisation project for API Equality, a San Francisco-based organisation empowering the LGBTQ API (Asian and Pacific Islander) communities. The project brief was to visualise displacement from the Castro neighbourhood, inspired by the Guardian’s "Bussed Out" story by Nadieh Bremer and Shirley Wu. I’m hoping this year to find another volunteering opportunity like this that makes good use of data skills.

 

What has been your path to power?

 

I graduated from the London School of Economics with a BSc in Business Mathematics and Statistics. While many of my classmates were going into banking and finance jobs, I didn’t feel inspired, but I wasn’t sure what else there was. My first job was as a data insight analyst at an advertising agency. I found myself enjoying the analytics element of the role, but I wasn’t passionate about advertising, especially via the agency model.

 

So, when I was approached by a recruiter about an analyst position for johnlewis.com I decided to make the switch to retail analytics, which was a great decision. I spent four years at John Lewis, then took a manager role at Marks & Spencer for another two years.

 

During that time, “data science” was becoming the new thing, and I took time to develop my data science skills, both in my job and in my own time. This gave me the confidence and skills to take the next step, which for me was a director of data science role at a digital agency where I led more creative applications of data science.

 

While there, Google approached me. I had always wanted to work for Google, so jumped at the chance. I’ve been at Google for nearly five years now with most of my time being spent leading product analytics teams within engineering on Google Play and Stadia.

 

What is the proudest achievement of your career to date?

 

One memorable achievement was a project I led for Danone while I was director of data science at DigitasLBi. The project involved scraping a huge amount of data from a forum, running advanced NLP techniques on it to detect topics and trends, then building an interactive tool to allow the client to explore the output and take action. It was a true team effort with a fantastic outcome that demonstrated the best of data science, while being interesting and enjoyable to work on.

 

Another thing I’m proud of is driving cultural change within the organisations I’ve worked for. It can be an uphill battle to change hearts and minds when it comes to using data, but really rewarding when you do.

 

Tell us about a career goal or a purpose for your organisation that you are pursuing?

 

I’ve been working to support and promote women in tech and data science both within Google and externally. I spoke at a Google-hosted Women in Data conference to inspire more women to break into the field or take their next career step. I’m a mentor to product analysts at Google and actively advocate for the job ladder, encouraging more candidates to make the move into the engineering world. Data science at Google has good diversity across the board but this declines with higher seniority and, ultimately, I’d like to see an increase in female representation in data science leadership.

 

How closely aligned to the business are data and analytics both within your own organisation and at an industry level? What helps to bring the two closer together?

 

I see Google used as an example in the media of a heavily data-driven company that other companies should aspire to. But, in my experience, even Google has a way to go in terms of data-driven decision-making. Both at Google and in the industry, the areas that generate revenue directly are much more likely to invest in, and rely upon, data and analytics.

 

Product areas that provide value indirectly might struggle to justify the investment in analytics and also need to work harder to prove the value that existing analytics brings. This overfocus on optimising revenue is short-sighted and I would love to see the industry develop better, more holistic product success metrics for user value, accessibility, inclusivity etc.

 

What is your view on how to develop a data culture in an organisation, building out data literacy and creating a data-first mindset?

 

It’s the role of any data team, in partnership with business leadership, to continually strive for better use and understanding of data and bring the data and business processes closer together. I have found the most success here when I’ve been able to lead by example. In practice this has meant becoming well integrated in the project process, identifying the opportunities where analytics can best drive decisions, then delivering robust and actionable analysis that the business has confidence in.

 

I’ve made sure that the business agrees upfront on taking action if the analysis outcome is X or Y. It’s important to ensure people have the right incentives to base their decisions on data, plus a positive environment where success and failure can be discussed openly without judgement.

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