Optimizing Customer Journeys with AI: A Deep Dive Video

Discover how artificial intelligence is shaping the future of commerce by offering tailor-made customer experiences. In this video, we first explore the fundamentals of AI and its role in commerce. Through a step-by-step approach, we detail how AI collects and analyzes customer data to make automated decisions. Two practical cases will then illustrate the real-world application of AI in providing relevant recommendations and interactions. Then, we will address the ethical challenges and implications of using AI. Concluding with the positive impact and benefits of a highly personalized customer experience. Join us for this informative deep dive and discover how to create revolutionary customer journeys with AI.

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Objectifs :

The training aims to help participants understand the role of artificial intelligence (AI) in personalizing customer journeys in commerce and to apply AI principles to enhance user experiences.

Chapitres :

  1. Introduction to Artificial Intelligence in Commerce
    Welcome to this training on the use of artificial intelligence to personalize customer journeys in commerce. Our goals today are straightforward: firstly, to understand the crucial role of AI in personalizing customer experiences, and secondly, to apply AI principles to create unique customer journeys and optimize user experience.
  2. Understanding Artificial Intelligence
    Before diving into the details, let's clarify what artificial intelligence is. AI refers to the use of machines to perform tasks that typically require human intelligence, including problem-solving, pattern recognition, and learning.
  3. The Importance of AI in Commerce
    Why use AI in commerce? The answer lies in its ability to analyze vast amounts of data and make predictions or recommendations that individualize interactions with each customer, thereby enhancing their shopping experience. AI examines customer data such as purchase history, browsing behavior, and interactions with customer service to anticipate their needs and expectations.
  4. Practical Examples of AI in Customer Journeys
    Let's explore some practical examples of AI applications in the customer journey. For instance, consider Lisa, a regular customer of an e-commerce site. AI analyzes her purchase history and browsing behavior, offering personalized recommendations based on her preferences and previously viewed items, thus increasing the likelihood of purchase. Another example is Tom, who seeks information on delivery. An AI-powered chatbot can interact with him, answer his questions, and guide him to products or special offers, creating a smooth and engaging customer experience.
  5. Implementing AI for Personalized Experiences
    Wondering how to put these principles into practice? Implementing an AI solution to improve customer journeys is a step-by-step process. First, data collection is crucial, where all relevant customer information, including demographic data, purchase histories, and website interactions, must be gathered and analyzed. Next is data analysis, where AI explores patterns and identifies trends to understand customer behaviors and preferences. Advanced algorithms, such as machine learning, play a vital role in this step, allowing AI to learn and adapt continuously.
  6. Automated Decision Making and Personalization
    The next step is automated decision-making. Based on the analysis, AI makes real-time choices about the best actions to take or recommendations to offer for each individual. This could involve sending a personalized email or offering discounts on relevant items. The final step concerns interaction and personalization, where automated decisions fuel highly personalized user experiences, allowing meaningful interaction with the customer at every touchpoint, thus enhancing their engagement and satisfaction.
  7. Case Study: Carla's Experience
    Let's explore a practical case. Imagine Carla, a customer who bought sports shoes a month ago. AI analyzes her previous interactions, recent browsing around sports items, and purchase history to create a user profile. Noting that Carla is interested in sports and has shown an increase in searches for yoga items, AI decides to send her an email with a special offer on a yoga set, creating an attractive and relevant experience for her.
  8. Reflection on AI Implementation
    Take a moment to reflect on how you could use AI to enhance customer experience in your context. Jot down your thoughts, and we will resume in 30 seconds.
  9. Challenges and Ethical Considerations
    Implementing AI also comes with challenges and ethical questions, such as data security, privacy, and user consent. It is imperative to navigate these waters carefully to ensure a transparent and ethical customer experience.
  10. Conclusion: The Power of AI in Customer Journeys
    AI is a powerful tool for enriching customer journeys by providing personalized, targeted, and engaging experiences. While implementation can be complex, the benefits in terms of customer satisfaction and loyalty are immense.

FAQ :

What is the role of AI in personalizing customer experiences?

AI plays a crucial role in personalizing customer experiences by analyzing large volumes of data to make predictions and recommendations tailored to individual customers, thereby enhancing their shopping experience.

How can AI improve customer journeys?

AI can improve customer journeys by collecting and analyzing customer data to understand behaviors and preferences, enabling personalized interactions and recommendations that enhance engagement and satisfaction.

What are some examples of AI applications in commerce?

Examples include personalized product recommendations based on purchase history, AI-powered chatbots that assist customers with inquiries, and targeted email offers based on user behavior.

What challenges come with implementing AI in customer journeys?

Challenges include ensuring data security, maintaining user privacy, obtaining user consent, and navigating ethical considerations related to AI usage.

How does machine learning contribute to AI in commerce?

Machine learning allows AI systems to learn from data patterns and adapt over time, improving the accuracy of predictions and recommendations for customers.

Quelques cas d'usages :

Personalized Product Recommendations

An e-commerce platform uses AI to analyze a customer's purchase history and browsing behavior to provide tailored product suggestions, increasing the likelihood of purchase.

AI-Powered Customer Support

A retail website implements an AI chatbot that interacts with customers, answering their questions and guiding them to relevant products or promotions, enhancing the overall shopping experience.

Targeted Marketing Campaigns

A company uses AI to analyze customer data and create personalized email marketing campaigns, offering discounts on items that align with individual customer interests, thereby improving engagement and sales.

Dynamic Pricing Strategies

An online retailer employs AI to adjust prices in real-time based on customer behavior and market trends, optimizing sales and customer satisfaction.

Customer Retention Strategies

A subscription service uses AI to analyze user engagement and identify at-risk customers, allowing the company to proactively reach out with personalized offers to retain them.

Glossaire :

Artificial Intelligence (AI)

The use of machines to perform tasks that normally require human intelligence, including problem solving, pattern recognition, and learning.

Customer Journey

The complete experience a customer has with a brand, from initial awareness through to purchase and beyond.

Data Analysis

The process of inspecting, cleansing, and modeling data to discover useful information, inform conclusions, and support decision-making.

Machine Learning

A subset of AI that involves the use of algorithms and statistical models to enable computers to improve their performance on a task through experience.

Automated Decision Making

The process where AI makes real-time choices based on data analysis to determine the best actions or recommendations for individual customers.

User Profile

A collection of information about a user, including their preferences, behaviors, and interactions, used to personalize experiences.

Ethical Questions

Concerns related to the moral implications of using AI, particularly regarding data security, privacy, and user consent.

résultat(s)
00:00:04
Welcome to this training
00:00:05
on the use of artificial
00:00:07
intelligence to personalize
00:00:08
customer journeys in commerce.
00:00:10
Our goals today are straightforward.
00:00:12
Firstly, you will understand the crucial role
00:00:15
of AI in personalizing customer experiences.
00:00:18
Secondly, you will be able to apply AI
00:00:20
principles to create unique customer
00:00:22
journeys and optimize user experience.
00:00:25
But before we dive into the details,
00:00:27
let's understand what
00:00:28
artificial intelligence is.
00:00:30
AI is the use of machines to perform tasks
00:00:33
that normally require human intelligence.
00:00:35
This can include problem solving,
00:00:37
pattern recognition and of course, learning.
00:00:40
Why use AI in commerce?
00:00:43
The answer lies in its ability to analyse
00:00:45
huge volumes of data and draw predictions
00:00:48
or recommendations to individualize
00:00:50
interaction with each customer,
00:00:51
thereby improving their shopping experience.
00:00:55
AI explores customer data such
00:00:57
as their purchase history,
00:00:58
browsing behavior and interactions
00:01:00
with customer service,
00:01:02
then uses this information to anticipate
00:01:05
their needs and expectations.
00:01:07
Now let's look at some practical examples
00:01:09
of AI application in the customer journey.
00:01:12
Imagine Lisa,
00:01:13
a regular customer of an e-commerce site.
00:01:16
AI analyzes her purchase history and browsing
00:01:19
behavior when she searches for a product.
00:01:21
AI offers personalized recommendations
00:01:23
based on her preferences and
00:01:25
previously viewed items,
00:01:27
thus increasing the chances of purchase.
00:01:29
Next, take Tom,
00:01:30
a customer seeking information on delivery.
00:01:33
Here,
00:01:33
an AI powered chat bot can interact with him,
00:01:36
answer his questions, and even guide
00:01:37
him to products or special offers,
00:01:39
creating a smooth and engaging
00:01:42
customer experience.
00:01:43
Wondering how to put these
00:01:44
principles into practice?
00:01:45
How?
00:01:45
How, concretely,
00:01:46
can AI be configured to offer
00:01:48
such personalized experiences?
00:01:50
Don't worry, in the next section we'll
00:01:52
break down an example step by step.
00:01:55
Implementing an AI solution to improve
00:01:57
customer journeys is a step by step process.
00:02:00
First,
00:02:01
data collection,
00:02:01
a crucial step where all relevant customer
00:02:05
information must be gathered and analyzed.
00:02:07
This includes demographic data,
00:02:09
purchase histories,
00:02:10
and interactions with the website.
00:02:13
Next comes data analysis, where
00:02:15
AI explores patterns and identifies
00:02:17
trends to understand customer
00:02:19
behaviors and preferences.
00:02:20
Advanced algorithms such as machine
00:02:22
learning play a crucial role in this step,
00:02:25
allowing AI to learn and adapt continuously.
00:02:28
The next step is automated decision making.
00:02:31
Based on the analysis,
00:02:33
AI makes real time choices about the
00:02:35
best actions to take or recommendations
00:02:37
to offer for each individual.
00:02:39
This could involve sending a
00:02:41
personalized e-mail or offering
00:02:43
discounts on relevant items.
00:02:45
The final step concerns
00:02:47
interaction and personalization.
00:02:48
Automated decisions fuel highly
00:02:51
personalized user experiences,
00:02:52
allowing meaningful interaction with
00:02:54
the customer at every touch point,
00:02:56
thus enhancing their engagement
00:02:59
and satisfaction.
00:03:00
Let's explore a practical case.
00:03:02
Imagine Carla, a customer who
00:03:04
bought sports shoes a month ago.
00:03:06
AI analyzes her previous interactions,
00:03:09
recent browsing around sports items,
00:03:11
and purchase history to create
00:03:13
a user profile.
00:03:14
AI,
00:03:14
noting that Carla is interested
00:03:16
in sports and having identified an
00:03:18
increase in searches for yoga items,
00:03:20
decides to send Carla an e-mail
00:03:22
with a special offer on a yoga set,
00:03:24
creating an attractive and
00:03:26
relevant experience for her.
00:03:28
Let's take a moment to reflect.
00:03:30
How could you use AI to enhance
00:03:32
customer experience in your context?
00:03:34
Jot down your thoughts and
00:03:35
we'll resume in 30 seconds.
00:04:06
Implementing AI also comes with
00:04:08
its share of challenges and ethical
00:04:10
questions such as data security,
00:04:12
privacy, and user consent.
00:04:14
It's imperative to navigate these
00:04:16
waters carefully to ensure a transparent
00:04:19
and ethical customer experience.
00:04:21
AI is a powerful tool for enriching
00:04:23
customer journeys by providing personalized,
00:04:25
targeted and engaging experiences.
00:04:28
While implementation can be complex,
00:04:30
the benefits in terms of customer
00:04:32
satisfaction and loyalty are immense.

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résultat(s)
00:00:04
Bem-vindo a esta formação
00:00:05
sobre a utilização de
00:00:07
Inteligência para personalizar
00:00:08
jornadas do cliente no comércio.
00:00:10
Nossos objetivos hoje são simples.
00:00:12
Em primeiro lugar, compreenderá o papel crucial
00:00:15
de IA na personalização das experiências dos clientes.
00:00:18
Em segundo lugar, você será capaz de aplicar IA
00:00:20
Princípios para criar um cliente único
00:00:22
jornadas e otimizar a experiência do usuário.
00:00:25
Mas antes de mergulharmos nos detalhes,
00:00:27
Vamos entender o que
00:00:28
a inteligência artificial é.
00:00:30
IA é o uso de máquinas para executar tarefas
00:00:33
que normalmente requerem inteligência humana.
00:00:35
Isto pode incluir a resolução de problemas,
00:00:37
reconhecimento de padrões e, claro, aprendizagem.
00:00:40
Por que usar IA no comércio?
00:00:43
A resposta está na sua capacidade de análise
00:00:45
grandes volumes de dados e previsões de desenho
00:00:48
ou recomendações para individualizar
00:00:50
interação com cada cliente,
00:00:51
melhorando assim a sua experiência de compra.
00:00:55
A IA explora os dados dos clientes, tais como
00:00:57
como seu histórico de compras,
00:00:58
Comportamento de navegação e interações
00:01:00
com atendimento ao cliente,
00:01:02
em seguida, usa essas informações para antecipar
00:01:05
as suas necessidades e expectativas.
00:01:07
Vejamos agora alguns exemplos práticos
00:01:09
de aplicação de IA na jornada do cliente.
00:01:12
Imagine Lisa,
00:01:13
um cliente regular de um site de comércio eletrônico.
00:01:16
IA analisa seu histórico de compras e navegação
00:01:19
comportamento quando ela procura um produto.
00:01:21
IA oferece recomendações personalizadas
00:01:23
com base nas suas preferências e
00:01:25
itens visualizados anteriormente,
00:01:27
aumentando assim as hipóteses de compra.
00:01:29
Em seguida, pegue Tom,
00:01:30
um cliente que procura informações sobre a entrega.
00:01:33
Aqui,
00:01:33
um bot de bate-papo alimentado por IA pode interagir com ele,
00:01:36
responder às suas perguntas, e até mesmo orientar
00:01:37
a produtos ou ofertas especiais,
00:01:39
criando um ambiente suave e envolvente
00:01:42
experiência do cliente.
00:01:43
Quer saber como colocar estes
00:01:44
princípios em prática?
00:01:45
Como?
00:01:45
Como, concretamente,
00:01:46
a IA pode ser configurada para oferecer
00:01:48
tais experiências personalizadas?
00:01:50
Não se preocupe, na próxima seção vamos
00:01:52
Divida um exemplo passo a passo.
00:01:55
Implementação de uma solução de IA para melhorar
00:01:57
O Customer Journeys é um processo passo a passo.
00:02:00
Em primeiro lugar,
00:02:01
recolha de dados,
00:02:01
um passo crucial onde todos os clientes relevantes
00:02:05
As informações devem ser recolhidas e analisadas.
00:02:07
Isto inclui dados demográficos,
00:02:09
históricos de compra,
00:02:10
e interações com o site.
00:02:13
Em seguida, vem a análise de dados, onde
00:02:15
A IA explora padrões e identifica
00:02:17
Tendências para entender o cliente
00:02:19
comportamentos e preferências.
00:02:20
Algoritmos avançados, como máquina
00:02:22
a aprendizagem desempenha um papel crucial nesta etapa,
00:02:25
permitindo que a IA aprenda e se adapte continuamente.
00:02:28
O próximo passo é a tomada de decisão automatizada.
00:02:31
Com base na análise,
00:02:33
A IA faz escolhas em tempo real sobre o
00:02:35
Melhores ações a tomar ou recomendações
00:02:37
para oferecer para cada indivíduo.
00:02:39
Tal poderá implicar o envio de um
00:02:41
e-mail personalizado ou oferta
00:02:43
descontos em itens relevantes.
00:02:45
A etapa final diz respeito
00:02:47
interação e personalização.
00:02:48
Decisões automatizadas são altamente alimentícias
00:02:51
experiências de utilizador personalizadas,
00:02:52
permitindo uma interação significativa com
00:02:54
o cliente em cada ponto de contacto,
00:02:56
aumentando assim o seu envolvimento
00:02:59
e satisfação.
00:03:00
Vamos explorar um caso prático.
00:03:02
Imagine a Carla, uma cliente que
00:03:04
comprou calçado desportivo há um mês.
00:03:06
A IA analisa suas interações anteriores,
00:03:09
navegação recente em torno de itens esportivos,
00:03:11
e histórico de compras para criar
00:03:13
um perfil de utilizador.
00:03:14
AI,
00:03:14
notando que Carla está interessada
00:03:16
no desporto e tendo identificado um
00:03:18
aumento das pesquisas por itens de yoga,
00:03:20
decide enviar um e-mail a Carla
00:03:22
com uma oferta especial em um conjunto de yoga,
00:03:24
criar um
00:03:26
experiência relevante para ela.
00:03:28
Vamos parar um pouco para refletir.
00:03:30
Como você poderia usar a IA para melhorar
00:03:32
Experiência do cliente no seu contexto?
00:03:34
Anote seus pensamentos e
00:03:35
retomaremos em 30 segundos.
00:04:06
A implementação da IA também vem com
00:04:08
a sua quota-parte de desafios e ética
00:04:10
questões como a segurança dos dados,
00:04:12
privacidade e consentimento do utilizador.
00:04:14
É imperativo navegar por estes
00:04:16
águas cuidadosas para garantir uma
00:04:19
e experiência ética do cliente.
00:04:21
A IA é uma ferramenta poderosa para enriquecer
00:04:23
jornadas do cliente, fornecendo personalizado,
00:04:25
experiências direcionadas e envolventes.
00:04:28
Embora a implementação possa ser complexa,
00:04:30
os benefícios em termos de cliente
00:04:32
A satisfação e a lealdade são imensas.

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