Datatist
Delivering World-Leading Predictive Marketing Cloud Products

Tougher economic conditions and the subsequent need for competitive differentiation, but more importantly the growing volumes of data are pushing organizations toward exploring newer avenues of leveraging predictive analytics in ways never done before. Sophia Song, Founder of Datatist, confabulates with us to explain the current state of predictive analytics and how her company can play a role in optimizing data for stimulating business growth.

What are the challenges that CIOs across the globe face in terms of predictive analytics?

For CIOs, concerns regarding how to analyze their data, automatically if possible, and turning that data into actionable insights to improve growth, engagement, and conversions are some of the biggest challenges. To do that, they are required to buy several products, which in addition to accruing into huge investments. Different applications deal with different business operations and produce a huge amount of data. This creates a complex business environment and enterprises usually fail to seamlessly integrate these applications and select the necessary data for analysis. Also, to handle their numerous advanced analytics applications, companies need highly skilled data scientists who as we all know are scarce in the market. What they are looking forward to is a one-stop solution that can tackle these challenges, but in reality, there has been no such product in the market for a long time.

How does Datatist help?

Datatist changes all that. With our software development kit (SDK), all user behavior data and marketing campaign data can be tracked and well organized into a big data platform, in real time. With the automatically built segmentation and predictive targeting models, Datatist enables the whole marketing campaign management process to optimize conversion rates. It does this for the whole of marketing lifecycle, from user acquisition and engagement to monetization, automatically and intelligently. Our solution does the job of a large data team in driving smart marketing. Typically what would be years of efforts, can now be done in a matter.

Can you please elaborate a bit more about your solution?

In the digital marketing technology landscape, there are two classes of entities—those who focus on AdTech (such as Google, Facebook, and LinkedIn) and the others who focus on MarTech. The latter class is further segmented into marketing analytics tools like Omniture from Adobe and marketing automation tools like Eloqua from Oracle and Pardot and ExactTarget from Salesforce. Though each of them is robust in its own terms, none of them connects marketing analytics to marketing automation. On the contrary, AI applications should be doing more than just providing better leads or targeting prospects that are likely to respond to marketing initiatives.

We are the first in the world to bridge this gap between marketing analytics and marketing automation. Leveraging ‘AI as a service’, Datatist can afford world-leading closed looped, one-stop predictive marketing cloud products which are much more expanded and can execute the whole process intelligently and automatically. These products can transform complicated data-driven marketing optimization processes—from data tracking, segmentation, predictive targeting, marketing campaign, and A/B test to campaign measurement—and optimize conversion rates for the entire marketing lifecycle, from user acquisition and engagement to monetization. However, we are not essentially a marketing automation product provider. We can support smart decisions like what is the optimal campaign targeting or content (intelligent), track the downstream effects of the campaign like the user on-site engagement and carry out conversion after the campaign (close looped).

What do your clients stand to benefit from such a product?

Predictive marketing cloud is a very powerful platform. Comparing this approach versus random marketing approaches, we have seen a lot of our customers being able to increase their marketing efficiency by as much as 10 times. We have noticed this among customers, both B2B and B2C, which are top players in their respective industries.

What are the challenges that CIOs across the globe face in terms of predictive analytics?

Molding AI technologies into an actual product is a very big challenge and it requires more than only broad and deep research experience in algorithms. It demands years of experience in making a product work in the industry and standardizing it to work in other industries as well. Datatist comprises a Ph.D. team from Silicon Valley with over ten years of experience and a robust track record of successful stints at big internet companies like eBay and LinkedIn, including but not limited to ten times lift in conversion rates and billions of discovered opportunities.

Datatist’s team is among the first in North America to have successfully investigated and implemented predictive marketing technologies in different industries. A strong research background in AI algorithms and years of experience in successful implementations are our key differentiating factors and they enable us to build solid predictive products suitable for a range of industries.