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Yigit Gungor, senior manager analytics, eBay

Yigit Gungor, senior manager analytics, eBay

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

 

eBay is among the early pioneers in ecommerce with an already well-established data and analytics culture embedded into the company DNA. We aim to be the partner of choice for our sellers and cultivate life-long trusted relationships with our buyers. We use data and analytics to offer the best possible experience for our buyers where we tailor the products and deals that spark unexpected joy. Similarly, we offer a wide range of analytical tools to our sellers to enhance their businesses and better serve their customers.

 

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

 

Quite early on, 2020 proved to be a challenging year for both our sellers and buyers, as well as our colleagues. With millions of sellers located around the world, when the initial lockdown in January hit our sellers in the APAC region, we moved away from previously planned activities and pivoted our buyer strategy and reallocated our resources in the direction of understanding and reacting to these rapid changes.

 

With the lockdowns announced by the UK government, we’ve seen a significant shift in buyer behaviour. eBay offered a deep inventory choice for buyers who were not able to source the goods in-store or online. During these early days, we quickly developed new algorithms to ensure that there was no price gauging going on in the platform for items in heavy demand.

 

UK lockdowns and restrictions translated into heightened activity for our seller community. However, unprecedented levels of uncertainty meant that predicting future demand became exceedingly challenging. In response to that, we’ve developed a new hybrid buyer cohort model that enables eBay to run various scenarios and plan for potential outcomes.

 

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

 

I expect 2021 to be the year where we will rewrite the rulebook on buyer engagement. In 2020, we saw significant shifts in buyer behaviour and it challenged some of the conventional wisdom on buyer engagement, loyalty, and promotions that have accumulated through years of experimentation. Therefore, 2021 will be the year of thinking differently, with a fresh mindset building on further experimentation to better understand the new rules of the game.

 

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

 

In 2020, in the early days of the UK lockdown, eBay partnered with the NHS, the Department of Health, and the Ministry of Defence to build a dedicated PPE portal to supply much-needed equipment to the NHS trusts and within a few days the portal started shipping PPE.

 

By the end of 2020, more than half a billion PPE items had been processed through the new portal. This agility and coordination were possible due to the exemplary collaboration between partners as well as eBay’s technology and expertise in data and analytics. As a company, we were founded on the principle of creating economic opportunity for all, I’m personally excited to see how eBay can continue to contribute to the wellbeing and needs of our community.

 

What has been your path to power?

 

I started my career as a forecasting analyst at GfK Boutique Research, providing market insight products to hedge funds and equity investors on the global electronics market outlook. I gained a lot of hands-on experience in building data products to address client needs, utilising vast global point of sale data, GfK collates from retailers worldwide.

 

After leading a team of analysts at GfK, I decided to accelerate my career and expand my industry experience and joined Capgemini Invent in its established analytics practice. As a management consultant equipped with data science skills, I worked with retail, consumer products, and government clients on data and analytics strategy, digital transformation projects and with established data science teams. I’ve also led the internal Capgemini supply chain analytics and data science communities, building data science proof of concepts which were rolled out as the new go-to-market propositions to clients.

 

After a few years of a rewarding career as a management consultant, I wanted a new challenge and decided to join eBay’s in-house analytics team and am currently leading marketing and buyer analytics for the UK.

 

What is the proudest achievement of your career to date?

 

I was working as a consultant to a major government department and our client was investigating the inbound call reasons for their newly introduced service. Previously, the organisation relied on either a sample of call logs or on a manual Excel sheet that logged the call reason, which was highly unreliable. In response to that, I analysed the unstructured audit log data to make sense of the events triggered by the contact centre agents during the call for every single call and then clustered them to come up with the estimated call reasons. Based on this insight, the department was able to pivot the direction and prioritise the digital transformation product roadmap accordingly.

 

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

 

eBay teams around the world have done an amazing job in building best in class applications of analytics projects, with hundreds of extremely talented data scientists and analysts working collaboratively. Although having its many strengths, being a global team brings its own challenges and different teams can easily end up looking at similar business problems through a slightly different lens. Personally, I’m in favour of methodology standardisation and building a cohesive approach together, therefore I do push my organisation for an alignment across different teams/regions where possible and valuable.

 

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 am proud to say that eBay puts customers at the heart of every decision it makes, and as an organisation, data and analytics are highly regarded within the business at all levels, including the senior management. Analytics informs our buyer and seller strategy, investment priorities, and policy decisions.

 

At eBay, we partner with our business stakeholders and work jointly towards our shared goals to create value for our customers. Our company culture is very collaborative and thrives by bringing diverse perspectives, backgrounds, and expertise for problem-solving and addressing key challenges.

 

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

 

I believe the key to building data literacy within an organisation starts with showing the art of the possible and creating excitement around the power of data. Today, the main challenge is not the lack of expertise or tools, it is establishing a good relationship with effective communication between the stakeholders and the teams building data insights.

 

As I’ve seen in many organisations, stakeholders with relatively low data literacy may not immediately see how data can help them address their issues. On the other hand, analysts can benefit from fully immersing themselves in the business and have a clear vision of business priorities, challenges, and needs. Only after establishing this connection and an understanding between business needs and data possibilities, this rewarding symbiotic relationship can foster good data literacy within an organisation.

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