Συνέντευξη με την Ronit Hanegby Ph.D
Wet-Water, Israel

• What is WetWater Company and what services and solutions can offer?
  
  WetWater provides Knowit and Marketit marketing automation applications for campaign planning that is aimed to support marketeers creating fast and fact-based ATL and BTL campaigns. Both applications enable to create Target Base Segmentation.
  
  Knowit brings big data closer to the end user by enabling to target the “right” customers and get insight about their behaviours and demographics the Knowit offers to build dynamic Macro & Micro segmentations. In intuitive way and without a former need in statistics the customer can drive campaigns and cover all customer base in quick and easy way.
  
  Marketit enables SMBs to target customers based on 3rd party data (such as coupons companies, credit cards and eCommerce). It brings the ability to utilize Data Base Marketing on a small scale and create campaigns via different platforms.
  
  We also provide Data Base Marketing consulting to worldwide companies that have intensive customer base (Telecom, Commercial and Investment Banking, Retail and Automotive).
  
  For these companies that are seeking fact based strategies and want to execute innovative and ongoing activities we offer a wide range of services.
  
  
• Do you have a software tool or platform you provide or only consulting services?
  
  We provide both platforms and range of professional services, including management consulting. All our consulting is based on data as we believe in FACT BASE and MEASURABLE consulting.
  
  Also, not every company is mature to install platforms and they need to outsource these types of activities. During the time we consult we are building with the customers the best infrastructure to answer their needs and make sure there is knowledge transfer to enable them to work with Knowit or other statistical software.
  
  
• What are the dynamics and trends in the next 3 years in Predictive and Business Analytics?
  
  Personally I believe that we will see two big trends within Predictive and Business Analytics. The enigma around “BIG DATA” and type of customers that will utilize data. As to Big Data we still need to see what is the value it will bring businesses and on what scale. There is a lot of developments in the area of Predictive Analytics that utilise and unifies behavioral data with external or internal sources. Within the same context the ability to understand the Digital Life Style of the customers will be a must in order to boost revenues and keep up businesses up-to-date with new trends that is involving social networks and devices.
  
  Another “hot” topic is the SMBs companies that are within the focus of Banks and Telco as well. There is not enough maturity within this segment that enable them to utilize Data Base Marketing abilities. I assume we will see new service developed specially for this segment.
  
  
• Digital life is everywhere. What are the critical points companies must pay attention using analytic tools?
  
  The definition of Digital Life Style (DLS) is based on the assumption that today the internet and the mobile devices defining customer based on the way they engaged with the technology. On one hand DLS is taking into account frequencies and volumes of data usage, type of application and web usage. On the other hand it must take into account the level of involvement within different types of digital activities. Most of this data does not exist beyond surveys. However, customers that are contributing to social network about their experiences are to be considered as opinion leaders as they affect many other customers. When companies want to approach this topic it will be useful to merge Behavioral Data, including all digital parameters with survey data.
  
  
  
• Do you think usage of personal data from customers and analysis of their behavior could be on a balance avoiding privacy misuse from any kind of company?
  
  I just read a very interesting research of Janet Vertesi, assistant professor of sociology at Princeton University about her experience to hide her pregnancy from Big Data.
  
  The bottom line is that hiding from big data is so inconvenient and expensive and she doesn’t recommend it as a lifestyle choice. This article is a proof that both sides have a lot to gain from using Big Data in a respectful manner. I personally believe that if the DNA of the marketeers is consisted on positive attitudes and constructs that the customers should gain a lot of benefits. So a strong policy within the companies about data protection and ethics is a must. Using segmentation and predictive analytics in a way that is not intrusive will build positive attitudes among consumers.