Synapse - Africa’s 4IR Trade & Innovation Magazine - 2nd Quarter 2021 Issue 12

Page 10

ADVERTORIAL

HUMAN IN THE SYSTEM:

Understanding customer behaviours with ecosystem.Ai

T

here’s a young man in a crowd of people in a small village. He’s holding a saxophone and he’s dying to play it. The problem this young man has is that he’s missing a vital part of the instrument - the mouthpiece. He’s been searching far and wide, to no avail, until one day he comes across an old woman who offers him a reading of his future. She informs him that she foresees that he will find what he is looking for soon enough, he glances down at the sax and fiddles with the hole where the mouthpiece should be. This old woman deduces what his heart most desires. She calls upon a merchant she knows well, and has worked with before, and tells him that if he can find the instrument’s missing part, they may just have a new customer. In the time when humans consulted oracles, and merchants knew their customers by name, trade was conducted almost entirely by means of personalisation and individual communication. These early forms of business conduct relied heavily on knowing your customer, and the same applied to matters of prediction. While merchants offered handpicked wares for their best customers, misty women

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SYNAPSE | 2ND QUARTER 2021

in large shawls offered grand futures to those they knew best. When the two worked together, they had the perfect business. Both trade and prediction, however, needed to evolve to accommodate customer base growth; and thus the close relationship between the offerors and the offerees was lost. The loss of individualisation though, did not change the fact that customers are unique - despite having been treated as such in broad spectrum sales. Business history has now come full circle. After years of data collection, it is now time to return to a place of personalisation. ecosystem.Ai, with the capabilities of machine learning, has found a way to extract human behaviour from data. Allowing companies to form stronger relationships with their customers, by understanding the clues in their behaviour. By being able to know your customer is behaving like a Jazz King, and communicating in a way that will resonate with them. ecosystem.Ai has been working tirelessly to create an effective set of tools, which companies can use to both understand, and engage, with their customers on a deeper level. Using the theory and practices of Computational Social Science, in conjunction with contemporary psychological constructs,

the chances of seeing the human in your data is not just a business dream. The practical implementation of dynamic behavioural analytics and segmentation, helps to progress common business practices beyond the static boundaries of mathematical analysis and categorisation. ecosystem.Ai offers a tripart selection of products: The ecosystem.Ai Workbench is a versatile, customisable user interface that reduces the complexity of machine learning processes. The Workbench is bolted directly into a business’s internal structure, maintaining exclusive privacy on company/ customer data. There are a vast number of capabilities available in the ecosystem.Ai workbench, including: project creation and management, data science engineering, model creation and deployment; amongst others. The second of the products is a series of pre-written algorithm Modules. These Modules can be used to solve common business problems (such as churn interventions or offer recommenders) using ecosystem.Ai’s behavioural constructs designed for a sector or exclusively for a company. Check out ecosystem.ai/#modules to find out more. The third product is The Client Pulse Responder which is a fully configurable and automated application that uses continuous re-enforcement learning. The Client Pulse Responder is the executable environment that ensures models are deployed, and results are seen. It is the internal core of ecosystem.Ai’s products, providing the space in which business problems are transformed into actionable solutions. The set of tools that ecosystem.Ai has developed equip clients with the knowledge and capacity to learn more about their customers. All of these elements help businesses see that collections of events in an individual’s life are unique enough to provide a view of the human in the data. ecosystem.Ai are the creator of the tools that contemporary merchants and oracles use in their merged business. By using the combination of business practice, the human sciences of social theory and psychology, and computational power; it is possible to reform the close relationship between company and customer. Understanding customer dynamics through data, offers the unique insight needed to know that your customer is behaving like a Jazz King.


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Articles inside

RPA: The Next Chapter In The Automation Story

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WizzPass Workspace Booking - Optimise & streamline your workspace management

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Invisio AI Scoops 3rd Place at 2020 SAB Foundation Social Innovation & Disability Empowerment Awards

2min
page 54

AI GONE GLOBAL: Why 20,000+ Developers from Emerging Markets Signed Up for GTC

3min
page 50

Nigerian insurtech startup Curacel raises $450k pre-seed round

1min
page 40

Clevva joins Blue Prism's Digital Exchange

2min
page 40

Smart Africa, Intel partner to build AI capacity building for African policymakers

1min
page 33

WITS, partners release AI-powered Algorithm To Detect SA’s Third COVID-19 Infection Wave

2min
page 32

UNESCO launches AI Needs Assessment Survey in Africa

3min
page 31

UMOJAHACK AFRICA 2021: Over 1 000 students participate in Africa’s largest inter-university hackathon

3min
page 30

ISHANGO, AIMS partnership to connect top African data scientists with international work experiences

2min
page 28

Liquid Telecom rebrands to Liquid Intelligent Technologies

1min
page 28

FROM GARAGE TO GLOBAL: How CompariSure’s conversational AI is driving digitisation within the Insurance industry

3min
pages 26-27

5 Steps To Building A People Analytics Function From The Ground Up

4min
page 25

Willis Re Launches new South Africa Hail Catastrophe Risk Model

3min
page 24

PUTTING AI INTO THE ENGINE ROOM

5min
page 23

First Fon to French Neural Machine Translation Engine launched

1min
page 16

TunBERT: InstaDeep, iCompass announce partnership on 1st AI-based Tunisian Dialect System

2min
page 16

Grassroots NLP community Masakhane wins Wikimedia Foundation Research of the Year Award

1min
page 6

How IBM Wants to Accelerate DX With Latest Breakthroughs in Hybrid Cloud, AI Capabilities

6min
pages 52-53

How the AU, Africa CDC will take On COVID-19 Through AI, Big Data

2min
page 48

DeepMind Establishes Scholarship for Wits Masters Students

2min
pages 49-50

Innovation Factory (Africa) Challenge

1min
page 51

Machine Learning Sandcastles

12min
pages 42-45

Automation 360: Automation Anywhere’s Cloud-Native Platform for Intelligent Automation

4min
pages 46-47

4 Reasons Why You Should Care About AI Governance Now

4min
page 41

Wits Announces Team to Advance AI Research in Africa

3min
page 39

SANRAL explores Machine Learning Applications for Road Safety, Congestion

2min
page 34

Siemens, CSIR partner to boost SA 4IR skills

2min
page 38

Strathmore Study Lays Bare Gender Inequality in African AI Industry

2min
page 35

How Quantum Computing Could Propel Us Light Years Into The Future

4min
pages 36-37

NVIDIA unveils its 1st Data Centre CPU

2min
page 22

NVIDIA Inception: Meet the African Startups Accepted Into the Programme

1min
page 33

How The Pandemic Gave Birth to SA’s latest 4IR SaaS platform

10min
pages 20-21

Meet UCT’s 1st Google Research Scholar Program Recipients

4min
pages 18-19

SA Team Places 2nd at 2021 Imagine Cup Junior Virtual AI Hackathon, Girls Edition

3min
page 17

These 3 African Startups Are Using AI, Data Science to Disrupt Fintech

1min
page 12

Why Kenya’s Ajua acquired AI/ ML fintech startup WayaWaya

3min
page 13

All You Need To Know About The EU’s DIGILOGIC initiative

5min
pages 8-9

Lacuna Fund invests $1m in Datasets for Low Resource African Languages

11min
pages 14-15

Human In The System: Understanding Customer Behaviours with ecosystem.Ai

3min
pages 10-11

Hyperautomation: A Case Study

3min
page 7

AfDB provides $1m Grant for AI-based National Consumer Management Systems

1min
page 6
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