Podcast EP 16 | Creating Brand Opportunities with Retail Data Intelligence: In Conversation with Galit Arizon, CEO at Pairzon

So that’s what pulled me from working from operating roles to build Pairzon in order to bring solution to retailers that I knew their pains and to be the solution. So together with Oded Mega, my Co-Founder and CTO, we founded Pairzon five or six years ago already and I brought the retail instinct to the business and he brought the technical depth and together we have built a platform that today serves over 150 retailers and this is the platform I wish I had for two decades.

Host: That’s an amazing journey, I must say. So let’s move to our second question for the day. With WeWork Labs, mentorship has become a key part of your journey. Could you share a few words on how mentoring others shaped your own entrepreneurial path?

Galit: Of course. So when I left my retail jobs in marketing, I actually went on the road and on the journey and I did not really know how to build it, how to meet investors, how to fundraise, how to generate their go-to market and how to get the right intros and what other do in that non-known space. So I had so many meetings with founders that each one of them allocated one or two hours in the beginning of my journey and gave so many advices and opened many relevant and significant intros that brought me and led me the first tools to build what I’m doing today.

So I decided to give back to the community and to give hours while being part of WeWork Labs to founders that, just like me, started their journey and were looking for advice. And sometimes it’s not about telling a founder whether or not their idea will be a success and generate a solution, but actually to think together to get back to the first-time builder instinct, just the way we started, and to be able to think, to stress thinking about the solution. And actually this is how I run Pairzon today in terms of getting close to the customers, resisting over-engineering, and those conversations actually contributed to me as well as they contributed to the founders.

Host: Yeah, that’s indeed a full circle to take on growth. So on that point, let’s check out what’s next. Pairzon is described as providing retailers with the power to see the future. How is this possible from a practical standpoint?

Galit: So, we serve retailers that have, as I said, a huge amount of data. And actually this data sits in silos and they have in-store data and online data and e-commerce data, etc. And all of this is all around.

So practically, Pairzon brings a unified dashboard of first-party purchase data from both in-stores and online in order to tie it to a single customer view. So instead of retailers watch transaction on Thursday and then another transaction of that same person on Friday and not being able to understand the customer profile, Pairzon ties it back to one real persona. And from there, our AI -powered analysis predicts segmentation, generates machine learning models such as RFM, customer lifetime value, basket analysis, customers who are about to churn.

And those predictions actually can be transformed into smart audiences that we predict that they are most likely to convert to commit a purchase. And then we decide, should we include those audiences, those users and the next campaign in what platform and tied to actual ROI back from the ad to their physical store in order to close the loop. So we’re finally connecting the data that was always there.

And this becomes the crystal ball of retailers.

Host: Yeah, that is amazing. It’s inspiring to know how you combine data and latest technologies to help retailers see the future. So taking the conversation further, there is always concern about data privacy when connected to consumer behavior. What are your thoughts on the same and how does Pairzon ensure compliance and build trust?

Galit: So, this is so relevant and so annoying to retailers. And obviously, privacy has to be an architecture and not an afterthought. So when we built Pairzon, we understand that we are dealing with first party data that a retailer already owns and has consent process.

And we were forcing ourselves to operate under GDPR and CCPA based on the jurisdictions that we provide services. And under those compliance, we understood that we have to share, to provide the ability to share those audiences in an anonymized and a secured way, which means that sharing data with brands, brands never see the individual identities, but only the ROI of those audiences that were generated directly from those campaigns or those specific banners. So at the end of the day, it’s about building trust.

And while the retailers you serve trust you that you will process the data based on the data privacy regulation, this is how they were able to scale and to let you process their data and handle it because they know that you’re doing it at least as carefully as they would.

Host: Yeah, that’s such an important point. And trust isn’t just a compliance checkbox; it’s the key to drive good data. So now let’s move to the next one. Pairzon creates opportunities for retailers to share anonymous audiences with brands. How does this model benefit the retailer and the brand partners? And how does it all go along?

Galit: As mentioned before, the retailers process a huge amount of data. And most of this data comes from the physical stores around 80 percent and 20 percent is in the e-commerce. And this enormous data is incredibly valuable and holds high intent customers audiences.

They never retailer had the ability to process it in a clean way and to monetize it without compromising trust. So, our retail media solution let retailers anonymously and securely activate those audiences and share them with the digital platforms and the social media platforms such as Mecca, Google, TikTok, etc. And then the retailer becomes the owner of new revenue based on the data they already collected.

And then they can share it with brand with precision targeted targeting instead of guesswork, which means that we offer a closed loop attribution so both sides can enjoy it and see the ROI without exposing sensitive data. And it’s actually ties it to real in-store and online purchases and not just clicks.

Host: Indeed, a win-win approach, I must say. And Pairzon is doing exceptionally in this regard. So, let’s take the conversation further. Retailers today are struggling with data fragmentation. How does Pairzon consolidate offline and online transactional data into our unified performance dashboard?

Galit: So, this is definitely a huge issue for retailers. Data fragmentation is something that actually generates the major problem in running customer profile, customer journey. So because of the fact that the data is scattered in the point of sale, in the POS transactional data and the e-commerce website and their marketing automation platform for email and text messages and in the social media and other digital channels, so they all, and obviously a loyalty program, so they all operate in silos.

And this is for the first time Pairzon brings first party data together into one platform that feeds the unified dashboard powered by real-time transactional data and allowing them to actually generate audiences based on the way that user behaves in an aggregated way with other same behavior of audience like these users in order to actually tie it to campaigns and measure their results and be able to see the full picture and not target you for example who just committed a purchase in the physical store with online including you and adding me because I’m now much relevant. So, we do this in one live accurate picture across every customer touch point offline and online.

Host: That surely gives a clearer view of the real pain point for so many retailers. So moving on to the next one, business wins with great partnerships. Could you discuss Pairzon’s collaboration with NVIDIA for an AI program for startups and how has this partnership been the key driver in the company’s growth?

Galit: So definitely NVIDIA was part of our initial journey and we are grateful for that. Being part of NVIDIA Inception program actually gave us the initial access to advanced compute and AI tooling that allowed us enable us to scale and accelerate in terms of providing our customers our retailers AI-based models that generated insights and let them see the growth and activate data in real time. So, this partnership actually been one of our key drivers behind the quick growth we’ve been experiencing and we are grateful for that.

Host: Partnerships often lead to great success and now moving to our final question for the day. What has it been like as a female founder in AI and retail tech? Any special difficulties you have encountered and what insights would you share with other women in this space?

Galit: So, I can tell you that this is my second venture and back then when I started and today as well the room is still often mostly men especially in AI fundraising. So I had to work harder to be taken seriously and to get credibility. So my decision on that was to always be super professional, come prepared and get ready for the meetings and know who you’re speaking to in the room and always deliver what you promise.

And my advice to women on that journey is just to go on you’re never 100% prepared. So go on the road, build first, fail fast and let the results speak.

Host: That’s an inspiring note to close Galit and with that we come to the end of our conversation. This has been such an insightful and energizing conversation. Thank you for joining us and sharing your journey for over two decades on the retail floor for building a platform that gives marketers a genuine roadmap on what’s next.

Thank you Galit.

Galit: Thank you so much. It’s been a pleasure speaking to you and have a wonderful day.

Host: And finally, we wrap up today’s discussion. To our audience who joined us for this interview episode, we are grateful for your support and thank you for tuning in. ExtraMile by YourTechDiet will be back with another insightful session soon.

Until then, keep exploring and keep learning.