Frank Factotum

Frank Factotum is an intelligent tool that allows you to use Artificial Intelligence to derive information from marketing and sales data more simply and intuitively.

Frank Factotum connects to the CRM and marketing automation software and allows for natural language interaction thanks to the identification of meta tags in the dataset.

Frank Factotum is based on the conception that the added value given by the end user is about data interpretation rather than the creation of reports using complex User Interfaces (UIs).

Furthermore, Frank Factotum comes with an advanced neural network that allows it to make previsions that are more accurate than the ones made by the CRM Software using traditional statistical tools. It is possible to use these forecasts in two ways:
– Asking them directly to Frank: “If we doubled the advertisement expenditure, which channel would present the highest ROI?”
– Using a proactivity function, which allows Frank to autonomously conduct simulations on data and identify potential opportunities and risks: “Advertisement campaigns on Google are doing good, but they may be optimized even more. You may want to check for keywords such as Artificial, Intelligence, Innovation, Technology.”

What it does

Understand natural language to interact with the company’s data
Frank Factotum is capable of understanding natural language and convert it into an input to communicate with the Marketing Automation and CRM software. The use of natural language as a mean of interaction removes the learning curve barrier, thus saving significant amounts of time and having the user focus only on the activities that create value.

Creation of forecasts about future scenarios using “White Box” Neural Networks and causal correlation
Frank Factotum can create future scenario analyses thanks to the AI networks developed by Divisible Global, more potent than the traditional prevision systems used by CRM and Marketing Automation software.
Divisible’s causal correlation algorithm is capable of identifying cause-effect relations within data (and not only mathematical ones, as happens with statistical correlation), while the White Box neural network provides a detailed overview of the most relevant variables that affect the end result.

Using proactivity to autonomously produce scenario simulations to identify potential opportunities and risks
Frank Factotum can autonomously simulate scenarios to immediately identify opportunities and risks that may happen thanks to its Proactivity function, all with settable custom goals that can act as guidelines for Frank’s analyses on the goodness of scenarios. For example, if we want to increase the e-commerce’s conversion rate, Frank can automate the creation of online campaigns optimized for that goal.

Supervised and Unsupervised Learning
Frank Factotum can learn to improve its predictive model as time passes, by comparing old forecasted data and actual data (supervised learning) and analyzing new data (unsupervised learning).

Customization of models through Hornet AI
Frank Factotum is capable of developing predictive models that answer to the primary needs of a company and is the result of years of field studies and experiences. But, since we know that every firm has different needs and preferences, we developed an integration with our Hornet AI technology for Frank Factotum that allows for the independent creation of machine learning models to answer to all the question that a company may have.

Data Storytelling: Optimized report creation
Frank Factotum can help the user in transforming the multitude of data into useful information to take effective decisions – one of the hardest challenges nowadays. Frank Factotum can recognize data types and guide the user in the creation of relevant and trustworthy reports.