Data-Driven Work Cultures: Raanan Eran of FORTVISION On How To Effectively Leverage Data To Take Your Company To The Next Level

An Interview With Pierre Brunelle

Set goals and collect data consistently. Achievable KPIs and metrics should be chosen with care and tracked, so that the collected data is relevant. A basic example for this is the goal of retaining employees. Many companies schedule yearly employee reviews to update the latter on their performance and ask of their satisfaction with the workplace. Employees can offer important feedback and insights, so it’s important to note if a comment is mentioned by more than one employee. In addition to employee review, organizations can offer employees a chance to provide anonymous feedback.

As part of our series about “How To Effectively Leverage Data To Take Your Company To The Next Level”, I had the pleasure of interviewing Raanan Eran, Founder and CEO of FORTVISION.

Raanan Eran is the Founder and CEO of FORTVISION, a Data-based Marketing Automation and Personalization platform. Prior to its foundation in 2016, Eran managed BI departments at several tech companies. Also, he holds an M.Sc. in Industrial Engineering from the Technion. Most importantly, Eran is an avid basketball fan.

Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

Thank you so much for having me.

I have always been drawn to technology and data. After serving as the Head of R&D team in the 8200 unit of IDF’s (Israeli Defense Forces) Intelligence Corp, I graduated with an M.Sc. in Industrial Engineering from the Israeli Institute of Technology. Later, I continued to manage BI departments at several technology companies.

All of this led me to start FORTVISION, a B2B marketing automation and personalization SaaS company.

Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?

When I just started FORTVISION, we did not have many customers. At one point, two of our clients could not pay us, so we ended up getting paid with ice cream and e-bikes, as these customers were ice cream and e-bike companies. We had way too much ice cream that we didn’t have enough storage space for, and no one used the e-bikes, so they just filled up the office. Lesson learned from this is, of course, try getting paid with real money and not with goods. And sometimes, it might even be worth it to say “no” to an opportunity.

Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?

I mainly enjoy reading biographies and motivational novels. One of my favorite novels is The Alchemist by Paulo Coelho. I read it in high school, and it eventually led me to start my own company. It convinced me that pursuing my dreams is worth any challenge I had, have, and will have along the way. I’m not one to believe signs and symbols, however this novel had some effect on me.

Are you working on any new, exciting projects now? How do you think that might help people?

Yes! My co-workers and I are constantly working on improving FORTVISION’s abilities and features. Now, we are working on adding CRM software to our platform. I believe that once companies have all their data not only connected in one place but also managed and equipped with actionable insights, they will be able to make much smarter business decisions. After the CRM is available, our customers will have an all-in-one platform of targeting and segmentation, marketing automation, personalization, programmatic advertising, and CRM.

Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization. So I’m particularly interested in this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?

Being data-driven basically means basing decision making on data. On a practical level, it means setting goals, tracking KPIs via data analytics, analyzing the raw data to derive insights and employing them to achieve said goals. In addition to company goals, each department needs to set its own goals.

Using segmentation, for example, human resources departments can collect and analyze data of the top performing and trustworthy employees to better characterize future recruits. Segmentation can also benefit departments like sales and marketing who can use it to target potential customers like the company’s top paying customers. Using Artificial Intelligence, financial advisors can base their investment predictions on smart algorithms. The more organizations use analytics relevant to their goals, the more data-driven they can become.

Which companies can most benefit from tools that empower data collaboration?

Whether an organization is an enterprise or a small business, any company can benefit from data — as banal as it sounds, data is power. Data collaboration tools can help companies with more than one touchpoint with their customers in terms of sales and marketing, but not only that. In bigger organizations, inter-department data collaborations allow sharing data easily across multiple departments for a smoother, cohesive workspace. Departments like R&D and QA, BI and IT can work more efficiently once their data is connected and shared in the same place. In SMBs, one could manage their entire business operations from one place, communicate with co-workers and customers alike and automate many processes.

We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.

Data analytics and data collaboration help increase efficiency and productivity. For example, instead of having meetings with manually made PowerPoint presentations, this data can be displayed in a shared dashboard for all the relevant parties to see during a weekly data-driven meeting. This information can be automatically fed into this dashboard by using a data automation tool.

By collecting online and offline data, companies can accelerate their digital transformation and manage every aspect of their business in one place, including tasks, customer support, operations, and strategic planning. By having all company data centered in one place, one can extract actionable data analytics and convert it into improvement of business KPIs and revenue growth.

One of our clients, a local gym, noticed many customers do not sign up for a second year after the first. Only around 25% of his customers renewed their subscription after the first year. So, they wanted to automatically retain first year active customers and re-engage the inactive ones. The gym sent us APIs with gym entries, which were analyzed against the CRM and ERP and leveraged to send messages to these customers. The APIs included data of physical gym entries using personal chips. The active customers received information about events at the gym, while the inactive customers were sent incentives and reminders to return to the gym.

Doing so improved the gym’s customer retention and experience significantly. In terms of customer experience, customers expect highly personalized experiences from brands and companies these days. By using data analytics and data collaboration, sales and marketing messages can be automatically sent to customers based on their real time behavior. Behavioral segmentation can help companies show their customers the content the latter want to see according to their demographics, purchasing history, hobbies and interests, etc. These insights then can be turned into real-time personalization and product recommendations.

Has the shift towards becoming more data-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?

For large organizations, one of the challenges is data overload. It can happen when there is too much data available within the business. Organizations can solve this challenge by implementing automation, Artificial Intelligence, and predictive software, which help clean and organize data. Using automations saves valuable time, helps increase productivity and create an efficient shared workspace. AI and machine learning offer predictive analytics that help using data to make based decisions.

Some organizations are also wary of data privacy, so they do not grant their employees access to basic data. The problem here is that all employees need access to at least basic data, as without it they will not be able to offer valuable data-based insights. The best solution is using data collaboration tools with various levels of access or showing each department its relevant key metrics.

Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.

1.Set goals and collect data consistently -

Achievable KPIs and metrics should be chosen with care and tracked, so that the collected data is relevant. A basic example for this is the goal of retaining employees. Many companies schedule yearly employee reviews to update the latter on their performance and ask of their satisfaction with the workplace. Employees can offer important feedback and insights, so it’s important to note if a comment is mentioned by more than one employee. In addition to employee review, organizations can offer employees a chance to provide anonymous feedback.

It’s worth noting that data must be constantly collected from every company source — online, offline, internal, sales, etc. and even available external databases. Data collaboration and visualization tools can offer valuable insights that sometimes cannot be seen without having all the data centralized in one place. For example, combining insights from website user activity and purchasing habits can help companies build a 360-degree view of their customers.

2.Make sure everyone is data literate -

Data should be deeply embedded into all organizational goals. Each department should be able to set goals and track the relevant metrics, however they will not be able to provide valuable insights unless they are data literate. That is especially true for C-level executives, who must lead the change towards a data-centric work culture and set goals and metrics for their employees to track and analyze. For example, if an executive cannot communicate to data scientists the exact metrics needed from them, then the data provided will have no value.

3.Segmentize customers to target prospects -

Analyzing customer behavior is crucial to understanding the company’s customers. Where they shop, what motivates them to purchase and what they want to see are just a few of the questions we should ask. By understanding customers, they can be retained, re-engaged if needed, and used to identify target customers by targeting prospects with the same behavior as current paying customers.

Analyze customer behavior by dividing customers into segments, and treat each segment personally, showing them what they want to see. Doing so, companies can increase customers’ average lifetime value and more. One of our customers, a pet supply online store, used segmentation to personalize their home page for different users. If a dog owner entered the site, they saw recommendations of dog food, toys, and other necessities. The same for cat owners. It helped improve their conversions by 34%.

4.Be creative —
As funny as it sounds when speaking of data — creativity is key. For example, quizzes, polls, and surveys can be used to gather data and apply it in sales and marketing messages.

A cosmetics company added a product matching quiz on their website to increase engagement and recommend products based on users’ personal preferences. This data, however, served more than that. It was collected, analyzed, and then used to send users personalized on-site messages, emails, SMS, and advertising, suggesting more products and content related to the users’ responses.

Quizzes, polls, surveys, and other engagement tools can help uncover valuable psychographic data for conversion optimization. For marketers wanting to serve their potential clients best, it’s safe to assume that the more data they have on a site visitor, the better. Demographic data only goes so far as to help with personalized content. Imagine if in addition to age and location, you could find out the person’s favorite color.

5.Be flexible -

If we take one thing from the pandemic — remember that everything is dynamic, so try being more open to new things and address changing business needs. At the beginning of its life, FORTVISION was only an advertising platform. However, once the pandemic started, many of our clients, most of which were advertising agencies, could not afford our services. We started researching other options until we arrived at the personalization and marketing automation ones. The change was not easy, even though the fields of advertising and marketing are not that different. Many of our previous clients were skeptical and did not want to try the new solutions. We had to change direction again. Finally, we arrived at the perfect solution — approaching eCommerce businesses with our platform. It worked, and most of our customers are eCommerce stores now. Adapt, readapt, and adapt again.

The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data Driven?

To help a work culture become more data driven, a combination of education and communication is needed. Employees need to feel comfortable using data to make decisions. It is the top-level executives’ responsibility to provide said education and to lead the change towards data culture by example.

It is vital that data is not simply collected but analyzed and applied according to the company’s goals. By having a list of necessary KPIs to track for each department, the organization can normalize data to employees.

It is also important to remember that this change does not occur overnight, so executives should not pressure employees to be data literate straight away but rather help them become more confident in employing data. This can be achieved by providing a system where employees can ask questions.

The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?

On the one hand, since the pandemic, you have more businesses accepting the digital transformation, physical shops turn to eCommerce, so data is definitely needed, and on the other hand, you have Email Privacy Acts like GDPR, while Google, Meta, and Apple are moving toward data privacy and a cookieless world. There is a battle between the need for data and the need for data privacy and cyber security. The need for data will continue to grow as will the need for data protection, so the outcome will probably be even more data collected, with an emphasis on cyber security and anonymity.

Does your organization have any exciting goals for the near future? What challenges will you need to tackle to reach them? How do you think data analytics can best help you to achieve these goals?

In addition to a new CRM software, we plan on implementing Artificial Intelligence capabilities in FORTVISION’s platform. With AI, the platform could learn the company’s data, of its customers, and recognize site visitors that are acting like paying customers. This will help us overcome the upcoming challenges involving data privacy — now, to differentiate between users and show them personalized content, we are tagging each user with a personal ID made of cookies and IP. Once FORTVISION has AI, the platform will be able to study customer and prospect behavior without the need for cookies.

It will take us some time to reach this goal, and many R&D and QA efforts. Data analytics will certainly help us once AI is implemented, as data will need to be collected and analyzed to start making smart predictions. Using AI will allow the platform to make predictions such as recognize prospects that are more likely to become customers.

How can our readers further follow your work?

Follow @FORTVISION on LinkedIn or subscribe to our newsletter, where we offer tips on how to leverage data.

Thank you so much for sharing these important insights. We wish you continued success and good health!

Thank you for the opportunity. Stay safe and data-driven!

About The Interviewer: Pierre Brunelle is co-CEO and Chief Product Officer (CPO) of Noteable, the collaborative notebook platform that enables teams to use and visualize data, together. Prior to Noteable, Brunelle led Amazon’s internal and SageMaker notebook initiatives. Pierre holds an MS in Building Engineering and an MRes in Decision Sciences and Risk Management.