*** The above indicators can be adjusting from time to time as our technologies evolve. ***
xPrdedit – eXposlogy Prediction by automated machine learning – is able to consume vast amounts of data to more accurately predict and identify who will attend the expos.
In a convolutional way, xProfiler cross-verifies, populates and updates the key information of expo attendee. It takes a continuous, incremental and self-propelled approach to refine data granularity.
Further toÂ xPredict result, xSegregator is designed to classify and separate the identities, e.g.: whether a show is a global one or national one, whether an attendee is a buyer or a normal participant.
Apart from the listed exhibitors, expo visitorÂ knows for the 1st time who else visitors that could matter to their business would also come together and should set the appointments with for meet up
Pick only the expos that can help make the most of attendance.
Get up to date information about exhibitor products and services.
Marketing and promotion of the event in the industry sector to a very precise list of audience.
Monetisation of additional services and advertising based on the big data.
Better designing of sponsorship programsÂ and other additional revenue streams.
Collection and analysis of statistical data.
Stay in close contact with participants and visitors all year round.
Pick only the expos that can maximize the ROI of exhibiting. Make the most of the limited exhibition budgets.
Know precisely who will be under the expo roof and how to drive the traffic to booth.
Reach out to the key visitors and set the appointments, months before expo.
Associations, industry news media, expo promotion bureaus, government.Â Expo app developers.
Stay informed of key industry figures. Analytics based on variousÂ metrics,Â better supported decision-making.
Keep in close contact with industry professionals all year round.
Promote the product to the industry sector in a more target way.
"It all started from a belief."
Initially, attendee prediction was just a belief but one day when looking over the mass data we had, I saw a spark inside of it which eventually gave birth to an innovative prediction theory.
That moment when Mario jumped from his seat, came up to me and excitedly talked about what he found from the data and his 'prediction' theory, I knew we were going to create something real big.
"Tech is fun."
Such a pleasure to work with 2 crazy guys, Mario & Cristiano! Along the way we transformed the big idea into models then algorithms, my life was being constantly fueled.