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AiThority Interview with Paul Sobel, President and CEO at Wodwo

AiThority Interview with Paul Sobel, President and CEO at Wodwo

Hi Paul, welcome to AIThority Interview Series. You come from a very enriching background in the data science technology industry. Please tell us a little bit about your journey and what inspired you to start Dataline and Wodwo.

Thank you, Sudipto. I started Dataline over twenty years ago as an information company centered around a consumer database of 230 million records. It was a natural extension of the work I had done at both Database America and Experian, where I was responsible for acquiring data sets that fed into the company’s’ consumer products. However, within a few years of the start of Dataline I felt the need to employ analytics to more effectively mine the Dataline database so we set up a data science department to build predictive models.

Model building can be a very labor-intensive activity taking our data scientists anywhere from one to two weeks to complete. With the development of the cloud, it became apparent that an online platform that could use artificial intelligence to enable non-technical users to build models at a fraction of the time it normally takes would be tremendously empowering.  In effect, we were attempting to replicate the process of model building in an environment that was not mediated by a data scientist.  The non-technical user could work directly with Wodwo to build models in under an hour. 

The last two years have accelerated digital transformation for businesses of all sizes and stature. What has been the biggest lesson for you that helped you stay on top of your business game? Would you like to share your pandemic experience on how you managed to grow your business, to focus on data science innovations, and to maintain customer relationships during the “uncertain times”?

Most of our employees work at the company HQ in Princeton, yet, once the pandemic hit, we, along with so many companies, were forced to work remotely. To my surprise, the transition was seamless.  In fact, because we were working remotely, we were in greater touch with one another and with our clients more so than we had been prior to the pandemic. Yet it was in this strange new environment that Wodwo was born.

It became apparent to us that the ease with which we were able to communicate and work effectively online could also be replicated in the way we build models.  If there was a paradigm shift in the way we were working as a company why couldn’t there be one in the way we were building models. Why did all of our models have to be built by data scientists?  Why couldn’t we leverage our intellectual property to build models through artificial intelligence?  Hence the birth of Wodwo.

Please tell us a little bit about Wodwo’s AI Audience Modelling platform for marketing teams. How is your AI platform different from the other SaaS-based data analytics platforms?

There are data platforms and there are modeling platforms, but I am not aware of any SaaS platform that combines the features of both in a non-technical environment.  

Wodwo has been specifically designed for marketers who want to build consumer audiences for prospecting.  Most modeling platforms require some technical knowledge or sophistication.  In addition, they require the user to access data from third parties. Wodwo asks nothing of the marketer but the ability to navigate a mouse through a series of user-friendly screens.  The user doesn’t need to access third party data because Wodwo comes with its own data furnished by Dataline.  The only thing required of the marketer is to upload 10,000 customer records. Wodwo uses that data to build look-alike models that will then be scored on the Dataline database, creating a prospecting audience.

Here’s how it works. Say the marketing team wants to create a digital audience based on its existing holiday customers. The team would upload a sample of 10,000 of those holiday customers in either a digital format (hashed e-mails) or an off-line format (name and address) to the platform. Wodwo would then match that data – it usually takes a minute and a half – to the Dataline database of 230 million records. Using the 2,000 data points on the Dataline database, Wodwo then produces a series of models which will replicate the demographic, psychographic and buying habits of the marketing team’s holiday customers. Once the database is scored, the marketing team can download a prospect audience of potential holiday buyers which it can market to.

How does Wodwo actually become a CMO’s first-party data-based marketing technology tool? What Kind of IT framework and investments are required to fully benefit from AI for marketing solutions?

The beauty of the Wodwo platform is that it requires no additional IT framework or investments.  It is literally plug and play.  Because Wodwo was designed to be as simple and user friendly as possible any marketing executive or CMO can build models and audiences from their desktops without the need to add additional staff or IT infrastructure.  About the only complicated part of the platform is making sure that the customer data is in the right format.  But Wodwo helps users with self-help videos explaining how to format your data correctly.

AI integrations take weeks if not months at an enterprise level to take shape and show results.  How do you accelerate AI adoption for the marketing teams that are looking for generate fast paced AI-driven customer insights and custom models in hours?         

As I mentioned in my previous response, Wodwo is designed to be plug and play.  By going through the self-help videos marketing execs can be up and running in minutes. Wodwo offers three subscription levels, with Enterprise being the richest.  But being the richest offering does not make it any more difficult to use.  It just offers more of what the user receives in the Advanced and Classic plans.

Each time the marketer uploads data to the platform, the data is matched to the consumer database.  As a result of that match the marketer receives a profile of the specific customers they’ve uploaded. Did they upload their best customers?  Did they upload customers with the best Life-Time Value? Wodwo returns graphs and charts illustrating the characteristics of each group.  Depending upon the plan they choose the marketer can select from five to twenty insights for each new data set.  Insights range from Age and Income to Offline and Online buying habits.  And what is especially nice is that because it takes only a minute and a half to match the data to the Dataline database, marketers are receiving insights about their customers in under two minutes.

Everything about the platform has been designed to be fast: from receiving customer insights in under two minutes to building models in under forty minutes.  The entire process – uploading data, receiving customer insights, building a model and downloading an audience – takes less than an hour.  Once you sign up you are ready to go. There is no down time.

Self-service dashboards and reporting tools are slated to become game-changers in business analytics. Please tell us how you see Wodwo wining in the Modern No-code business analytics with your powerful AI engine.

As I mentioned previously, Wodwo was designed to be easy and simple to use. The only way we could achieve that was by making sure that the user would never have to worry about coding or, for example, employing unit testing.  We don’t expect marketers to be able to code – that’s our job.  What they need to do is concentrate on achieving their marketing goals with the right tool.

Because coding is not a part of the platform, we are anticipating additional user needs in our release of Wodwo 2.0, which will have greater functionality. The release, which we are currently working on, will allow marketers to build models on their own data sets as well as to build different types of models.  For example, 2.0 will allow marketers to reactivate dormant customers and optimize existing customers and prospects.  It will allow marketers to build response models in addition to customer models. But all of this will be done with a series of easy-to-use screens that will be self-contained.  The marketer will never have to worry about writing code because the code is all inside the platform.

Could you tell us about one customer win that you are most proud of? How did it help your company grow to the next level of innovation and customer service.  

Dataline received a bid to install the database with a major Financial Services Company. After several months of testing large data sets the company awarded a very big contract to Dataline.  The revenue resulting from the contract enabled Dataline to concentrate its R&D efforts on developing cutting edge modeling techniques. Ultimately, those cutting-edge modeling techniques were used in developing the artificial intelligence behind Wodwo.  So what began as a simple database installation resulted in the development of a ground-breaking AI platform.

How big is your AI and machine learning engineering team?

The team consists of approximately seven members: three Data Scientists, a Senior Software Engineer, a Systems Architect, a DevOps Engineer, and a Technical Architect.

From an industry perspective, what kind of steps are you taking at Wodwo to regulate AI efforts? What are your initiatives in AI ethics/responsible AI?

Privacy is critical to Wodwo, and we take that responsibility seriously. At Wodwo, privacy operates on multiple fronts: protecting the data clients upload and ensuring that consumers have a choice and can opt out of the database. 

When a user uploads a portion of their client file they are trusting that their precious asset will be protected.  The client data is needed in the modeling process but once the data is matched to the database all client records are destroyed.  The only vestige remaining is a unique id, which is used in the modeling process and is used to make sure that when Wodwo builds an audience it is automatically removing any client records.

For consumers who would like to have their names removed from the 230 million database, all they need do is go to the Privacy Page and either e-mail or phone us to have their name removed from the database.  All requests are honored with 24 hours.

In addition, when users register for a subscription they must agree to abide by the terms set forth by Wodwo with a strict list of do’s and don’ts. 

Your take on the future of AI and NLP operations and how big the industry will become by 2025 for Cloud and SaaS businesses?

Based on my reading of the literature, AI continues to grow very nicely, with predictions of growth reaching anywhere from $35 to $37 billion in the US by 2025.  In fact, the global market for AI is north of $300 billion already and it, too, continues to grow at a rate of 17th percent. AI positions listed on LinkedIn doubled in one year alone.  All indications are the AI market is poised to continue its ascent as evidenced by the increased demand for positions requiring knowledge of AI to the increased proliferations of AI platforms, such as Wodwo.  It is only natural that users will continue to demand the speed, accuracy and cost savings that AI platforms can provide.

Any advice to every data science/AI professional looking to start in this space:

Our chief data scientist, and the one responsible for the development of Wodwo’s AI, didn’t believe that a platform could be developed that would compete with models built by data scientists.  Ironically, although he was the principal naysayer, he would up creating an AI modeling platform that is every bit as good and, in many ways, superior to those models built by hand.  However, rather than, signaling the death knoll of the profession it actually invigorates it.  By removing the boring, mundane tasks in building a model — like variable elimination — AI allows data scientists to concentrate on tasks that require greater higher-level thinking and creativity.  So rather than eliminating the need for data scientists, AI actually reinforces that need.  Data science will continue to be a strong growth profession.

Thank you, Paul! That was fun and we hope to see you back on soon.

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Paul Sobel serves as President and Chief Executive Officer of both Dataline and its affiliate, Wodwo. His professional career in the Information Industry spans 35 years. Prior to founding the two companies, Paul held senior level management positions at Experian, Metromail, and Database America in the areas of data compilation, licensing, acquisition, sales, and electronic media. He has successfully built, managed and maintained some of the industries’ largest consumer and business databases.

As President and CEO of Dataline, Paul oversees the firm’s daily operations, setting the strategic direction of the company. In addition, Paul is responsible for the creation, compilation and management of Dataline’s consumer database, and the Dataline, publishing, catalog and non-profit cooperative databases.

In 2022, Paul founded Wodwo, a revolutionary AI marketing and analytics self-serve SaaS and DaaS Platform that allows users to build models in under one hour.  Powered by Dataline, Wodwo’s AI Modeling Database has over 230,000,000 modeled individuals. Paul is now setting the direction for a new release of Wodwo to be launched in early 2023.

Paul holds a B.A. from Brandeis University and an A.M. from the University of Michigan. He was a Ph.D. candidate at The Johns Hopkins University and holds an MBA from New York University.


Wodwo is to discover the AI-powered platform that will forever change how you acquire new customers. Powered by DatalineAI – an industry expert in data science – Wodwo was built to simplify customer modeling for marketers. Create custom modeled audiences based on your best customers by generating targeted audiences based on the actual buying behaviors of your customers. Wodwo produces the same high-quality custom audience models that used to take us weeks to build on our own.

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