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Revolution of Open-source and film making towards open film making
6 octobre 2011, par kent1
Mis à jour : Juillet 2013
Langue : English
Type : Texte
Autres articles (44)
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Publier sur MédiaSpip
13 juin 2013Puis-je poster des contenus à partir d’une tablette Ipad ?
Oui, si votre Médiaspip installé est à la version 0.2 ou supérieure. Contacter au besoin l’administrateur de votre MédiaSpip pour le savoir -
HTML5 audio and video support
13 avril 2011, par kent1MediaSPIP uses HTML5 video and audio tags to play multimedia files, taking advantage of the latest W3C innovations supported by modern browsers.
The MediaSPIP player used has been created specifically for MediaSPIP and can be easily adapted to fit in with a specific theme.
For older browsers the Flowplayer flash fallback is used.
MediaSPIP allows for media playback on major mobile platforms with the above (...) -
Support audio et vidéo HTML5
10 avril 2011MediaSPIP utilise les balises HTML5 video et audio pour la lecture de documents multimedia en profitant des dernières innovations du W3C supportées par les navigateurs modernes.
Pour les navigateurs plus anciens, le lecteur flash Flowplayer est utilisé.
Le lecteur HTML5 utilisé a été spécifiquement créé pour MediaSPIP : il est complètement modifiable graphiquement pour correspondre à un thème choisi.
Ces technologies permettent de distribuer vidéo et son à la fois sur des ordinateurs conventionnels (...)
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B2B Customer Journey Map : A Quickfire Guide for Growth
20 mai 2024, par ErinWhat is a company’s biggest asset ?
Its product ? Its employees ? Its unique selling proposition ?
More and more people are recognising it’s something else entirely : your customers.
Without your customers, your business can’t exist.
Nearly 77% of B2B buyers found the buying process too complicated.
With more competition than ever, it’s crucial you provide the best possible experience for them.
That’s where your customer journey comes in.
If you’re in the B2B space, you need to know how to map out the journey.
By building a B2B customer journey map, you’ll be able to analyse the weak spots in the customer journey so you can improve the experience (and generate more revenue).
In this article, we break down the B2B customer journey stages, how to build a customer journey map and how Matomo can help you track your customer journey automatically.
What is a B2B customer journey ?
Every customer goes through a specific path within your business.
At some point in time, they found out about you and eventually bought your products.
A B2B customer journey is the collection of touchpoints your customer has with your business from start to finish.
From discovery to purchase (and more), your customers go through a specific set of touches you can track. By analysing this journey, you can get a snapshot of your user experience.
One way to track the customer journey is with a B2B customer journey map.
It helps you to quickly see the different steps your customers take in their path with your business.
With it, you can quickly identify weak spots and successes to improve the customer journey.
5 stages of the B2B customer journey
Every one of your customers is unique. Their specific needs and their journey.
It’s all different.
But, there are crucial steps they take through their journey as your customer.
It’s the same path your entire customer base takes.
Here are the five stages of the B2B customer journey (and why you should track them) :
1. Awareness
Awareness is the first stage that every B2B buyer goes through when they start their journey in B2B companies as a customer.
At this stage, your target buyer understands they have a problem they need solving. They’re out, actively trying to solve this problem.
This is where you can stand out from the competition and give them a good first impression.
Some helpful content you could create to do this is :
- Blog posts
- Social media posts
- Ebooks
- Whitepapers
2. Consideration
Next up, your buyer persona has an awareness of your company. But, now they’ve started narrowing down their options for potential businesses they’re interested in.
They’ve selected yours as a potential business to hand their hard-earned cash over to, but they’re still making up their mind.
At this point, you need to do what you can to clear up any objections and doubts in their mind and make them trust you.
Some helpful content you could create here include :
- Product demos by your sales team
- Webinars
- Case studies
3. Conversion
Next up, your target buyer has compared all their options and decided on you as the chosen product/company.
This is where the purchase decision is made — when the B2B buyer actually signs or clicks “buy.”
Here, you’ll want to provide more :
- Case studies
- Live demos
- Customer service
- Customer reviews/testimonials
4. Loyalty
Your B2B buyer is now a customer. But, not all customers return. The majority will slip away after the first purchase. If you want them to return, you need to fuel the relationship and nurture them even more.
You’ll want to shift your efforts to nurturing the relationship with a post-purchase strategy where you build on that trust, seek customer feedback to prove high customer satisfaction and reward their loyalty.
Some content you may want to create here includes :
- Thank you emails
- Follow-up emails
- Follow-up calls
- Product how-tos
- Reward program
- Surveys
5. Advocacy
The final stage of the B2B customer journey map is advocacy.
This is the stage beyond loyalty where your customers aren’t just coming back for more ; they’re actively telling others about you.
This is the cream of the crop when it comes to the B2B buyer stages, and it happens when you exceed customer expectations repeatedly.
Your goal should be to eventually get all of your customers to this stage. Because then, they’re doing free marketing for you.
This is only possible when a customer receives enough positive B2B customer experiences with your company where the value they’ve received far exceeds what they perceived they have given.
Here are a few pieces of content you can create to fuel advocacy :
- Surveys
- Testimonial requests
- Referral program
Difference between B2C and B2B customer journeys
Every person on earth who buys something enters the customer journey.
But, not all customer journeys are created equal.
This is especially true when you compare the B2C and B2B customer journeys.
While there are similarities, the business-to-consumer (B2C) journey has clear differences compared to the business-to-business (B2B) journey.
The most obvious difference between the two journeys is that B2B customer journeys are far more complex.
Not only are these two companies selling to different audiences, but they also have to deploy a completely different set of strategies to lead their customers down the path as far as they can go.
While the journey structures are similar (from awareness to advocacy), there are differing motivating behaviours.
Here’s a table showing the difference between B2C and B2B in the customer journey :
Different Factors B2B B2C Target audience Smaller, industry more important Larger, general consumer Buyer Multiple decision-makers One decision-maker Buying decision Based on needs of the organisation with multiple stakeholders Based on an individual’s pain points Buying process Multiple steps Single step Customer retention Organisational needs and ROI-based Individual emotional factors Repeat sales driver Deep relationship Repetition, attention-based Step-by-step guide to building a B2B customer journey map
Now that you’ve got a basic understanding of the typical B2B customer journey, it’s time to build out your map so you can create a visual representation of the journey.
Here are six steps you need to take to craft an effective B2B customer journey map in your business :
1. Identify your target audience (and different segments)
The first step in customer journey mapping is to look at your target audience.
You need to understand who they are and what different segments make up your audience.
You need to look at the different roles each person plays within the journey.
Unlike B2C, you’re not usually dealing with a single person. You likely have a few decision-makers you need to interact with to close a deal.
The average B2B deal involves 6 to 10 people.
Analyse the different roles and responsibilities of your audience.
Figure out what requirements they need to onboard you. Understand each person’s level of influence in the buying decision.
2. Determine your customers’ goals
Now that you have a clear understanding of each person involved in the buying process, it’s time to analyse their unique needs and goals.
Unlike B2C, which will include a single person with a single set of needs and goals, you have to look at several people through the decision-making process.
What is every decision-maker’s goal ?
An entry-level admin will have much different goals than a CEO.
Understand each of their needs as it will be key to selling them and taking you to the next person in the chain of command.
3. Lean on data and analytics
Now it’s time to analyse your data.
You don’t want to guess what will work on your B2B buyers. Instead, leverage data that proves what’s working (and what’s not).
Analytics software like Matomo are crucial tools in your B2B customer journey toolkit.
Matomo can help you make data-driven decisions to fuel customer acquisition and loyalty to help get more customers all the way to the advocacy stage.
Using Matomo (which analyses and interprets different data sources) can give you a holistic view of what’s going on at each stage of the journey so you can reach your goals.
Try Matomo for Free
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4. Draw out customer journey stages
Now that you have your data-backed plan, it’s time for some customer journey mapping.
You can do this on paper or use a diagram tool to create a visual B2B customer journey map.
Here, you’ll draw out every single stage in your customer journey, including every single touchpoint from different decision-makers.
5. Determine each customer touchpoint
Once you’ve drawn up the customer journey stages, you’ll have a key list of B2B customer journey touchpoints to implement.
Write down every single customer interaction possible on the journey through.
This could be reading an email, a blog post or watching a video on your home page.
It could be an advertisement, a phone call or a follow-up email.
It could even be a live demo or video sales call (meeting).
6. Identify your own goals
Now that you’ve got your visual B2B customer journey mapping done, it’s time to go back to you and your company.
What are your goals ?
What are the end results you’re looking for here ?
You’ve got your current map in place. Now, how would you like customers to go through this journey ?
Where would you like them to end up ?
Look back at your company’s primary objectives if you’re stuck here.
If your company is looking to increase profit margins, then maybe you want to focus more on retention, so you’re spending less on acquisition (and leaning more on recurring revenue from existing customers).
How to create a Matomo funnel to track your B2B customer journey
If you want to start tracking and optimising your B2B customer journey, you need to have a good grasp on your funnel.
The reality is that your customer journey is your funnel.
They’re one and the same.
Your customer journeys through your sales funnel.
So, if you want to optimise it, then you need to see what’s going on at each stage of your funnel.
With Matomo, you can map out your entire funnel and track key events like conversions.
This allows you to identify where your site visitors are having problems, where they’re exiting and other obstacles they’re facing on their journey through.
To start, you first define what events or touchpoints you want included. This could mean :
- Landing on your website
- Visiting a product page
- Adding something to cart
- Going to checkout
- Clicking “buy”
Then, at each stage, you’ll see conversion rates.
For example, if only 3% of your visitors go from landing on your website to the product page, you likely have an issue between your homepage (and other pages) and your product pages.
Or, if you can get people to add to cart, but you rarely get people going to checkout, there’s likely a problem to fix on your add-to-cart page.
By leveraging Matomo’s funnels feature, you get to see your entire customer journey (and where people are falling off) so you understand what you need to optimise to grow your business.
If you’re ready to start building and optimising your customer journey today, then try Matomo for free for 21 days.
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21 day free trial. No credit card required.
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Converting konvajs state to Advanced SubStation Alpha (ASS) format for subtitles
7 juillet 2024, par AhsanI am building a subtitle editor using react.js. I plan to use konvajs to build the styling feature of editor like rotate subtitles, change size etc. How do I convert resultant konva state to ass format so that ffmpeg can render these subtitles on video.


If there is a better solution than using konvajs then please guide me.


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How HSBC and ING are transforming banking with AI
9 novembre 2024, par Daniel Crough — Banking and Financial Services, Featured Banking ContentWe recently partnered with FinTech Futures to produce an exciting webinar discussing how analytics leaders from two global banks are using AI to protect customers, streamline operations, and support environmental goals.
Watch the on-demand webinar : Advancing analytics maturity.
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</script>Meet the expert panel
Roshini Johri heads ESG Analytics at HSBC, where she leads AI and remote sensing applications supporting the bank’s net zero goals. Her expertise spans climate tech and financial services, with a focus on scalable analytics solutions.
Marco Li Mandri leads Advanced Analytics Strategy at ING, where he focuses on delivering high-impact solutions and strengthening analytics foundations. His background combines analytics, KYC operations, and AI strategy.
Carmen Soini Tourres works as a Web Analyst Consultant at Matomo, helping financial organisations optimise their digital presence whilst maintaining privacy compliance.
Key findings from the webinar
The discussion highlighted four essential elements for advancing analytics capabilities :
1. Strong data foundations matter most
“It doesn’t matter how good the AI model is. It is garbage in, garbage out,”
Johri explained. Banks need robust data governance that works across different regulatory environments.
2. Transform rather than tweak
Li Mandri emphasised the need to reconsider entire processes :
“We try to look at the banking domain and processes and try to re-imagine how they should be done with AI.”
3. Bridge technical and business understanding
Both leaders stressed the value of analytics translators who understand both technology and business needs.
“We’re investing in this layer we call product leads,”
Li Mandri explained. These roles combine technical knowledge with business acumen – a rare but vital skill set.
4. Consider production costs early
Moving from proof-of-concept to production requires careful planning. As Johri noted :
“The scale of doing things in production is quite massive and often doesn’t get accounted for in the cost.”
This includes :
- Ongoing monitoring requirements
- Maintenance needs
- Regulatory compliance checks
- Regular model updates
Real-world applications
ING’s approach demonstrates how banks can transform their operations through thoughtful AI implementation. Li Mandri shared several areas where the bank has successfully deployed analytics solutions, each benefiting both the bank and its customers.
Customer experience enhancement
The bank’s implementation of AI-powered instant loan processing shows how analytics can transform traditional banking.
“We know AI can make loans instant for the customer, that’s great. Clicking one button and adding a loan, that really changes things,”
Li Mandri explained. This goes beyond automation – it represents a fundamental shift in how banks serve their customers.
The system analyses customer data to make rapid lending decisions while maintaining strong risk assessment standards. For customers, this means no more lengthy waiting periods or complex applications. For the bank, it means more efficient resource use and better risk management.
The bank also uses AI to personalise customer communications.
“We’re using that to make certain campaigns more personalised, having a certain tone of voice,”
noted Li Mandri. This particularly resonates with younger customers who expect relevant, personalised interactions from their bank.
Operational efficiency transformation
ING’s approach to Know Your Customer (KYC) processes shows how AI can transform resource-heavy operations.
“KYC is a big area of cost for the bank. So we see massive value there, a lot of scale,”
Li Mandri explained. The bank developed an AI-powered system that :
- Automates document verification
- Flags potential compliance issues for human review
- Maintains consistent standards across jurisdictions
- Reduces processing time while improving accuracy
This implementation required careful consideration of regulations across different markets. The bank developed monitoring systems to ensure their AI models maintain high accuracy while meeting compliance standards.
In the back office, ING uses AI to extract and process data from various documents, significantly reducing manual work. This automation lets staff focus on complex tasks requiring human judgment.
Sustainable finance initiatives
ING’s commitment to sustainable banking has driven innovative uses of AI in environmental assessment.
“We have this ambition to be a sustainable bank. If you want to be a sustainable finance customer, that requires a lot of work to understand who the company is, always comparing against its peers.”
The bank developed AI models that :
- Analyse company sustainability metrics
- Compare environmental performance against industry benchmarks
- Assess transition plans for high-emission industries
- Monitor ongoing compliance with sustainability commitments
This system helps staff evaluate the environmental impact of potential deals quickly and accurately.
“We are using AI there to help our frontline process customers to see how green that deal might be and then use that as a decision point,”
Li Mandri noted.
HSBC’s innovative approach
Under Johri’s leadership, HSBC has developed several groundbreaking uses of AI and analytics, particularly in environmental monitoring and operational efficiency. Their work shows how banks can use advanced technology to address complex global challenges while meeting regulatory requirements.
Environmental monitoring through advanced technology
HSBC uses computer vision and satellite imagery analysis to measure environmental impact with new precision.
“This is another big research area where we look at satellite images and we do what is called remote sensing, which is the study of a remote area,”
Johri explained.
The system provides several key capabilities :
- Analysis of forest coverage and deforestation rates
- Assessment of biodiversity impact in specific regions
- Monitoring of environmental changes over time
- Measurement of environmental risk in lending portfolios
“We can look at distant images of forest areas and understand how much percentage deforestation is being caused in that area, and we can then measure our biodiversity impact more accurately,”
Johri noted. This technology enables HSBC to :
- Make informed lending decisions
- Monitor environmental commitments of borrowers
- Support sustainability-linked lending programmes
- Provide accurate environmental impact reporting
Transforming document analysis
HSBC is tackling one of banking’s most time-consuming challenges : processing vast amounts of documentation.
“Can we reduce the onus of human having to go and read 200 pages of sustainability reports each time to extract answers ?”
Johri asked. Their solution combines several AI technologies to make this process more efficient while maintaining accuracy.
The bank’s approach includes :
- Natural language processing to understand complex documents
- Machine learning models to extract relevant information
- Validation systems to ensure accuracy
- Integration with existing compliance frameworks
“We’re exploring solutions to improve our reporting, but we need to do it in a safe, robust and transparent way.”
This careful balance between efficiency and accuracy exemplifies HSBC’s approach to AI.
Building future-ready analytics capabilities
Both banks emphasise that successful analytics requires a comprehensive, long-term approach. Their experiences highlight several critical considerations for financial institutions looking to advance their analytics capabilities.
Developing clear governance frameworks
“Understanding your AI risk appetite is crucial because banking is a highly regulated environment,”
Johri emphasised. Banks need to establish governance structures that :
- Define acceptable uses for AI
- Establish monitoring and control mechanisms
- Ensure compliance with evolving regulations
- Maintain transparency in AI decision-making
Creating solutions that scale
Li Mandri stressed the importance of building systems that grow with the organisation :
“When you try to prototype a model, you have to take care about the data safety, ethical consideration, you have to identify a way to monitor that model. You need model standard governance.”
Successful scaling requires :
- Standard approaches to model development
- Clear evaluation frameworks
- Simple processes for model updates
- Strong monitoring systems
- Regular performance reviews
Investing in people and skills
Both leaders highlighted how important skilled people are to analytics success.
“Having a good hiring strategy as well as creating that data literacy is really important,”
Johri noted. Banks need to :
- Develop comprehensive training programmes
- Create clear career paths for analytics professionals
- Foster collaboration between technical and business teams
- Build internal expertise in emerging technologies
Planning for the future
Looking ahead, both banks are preparing for increased regulation and growing demands for transparency. Key focus areas include :
- Adapting to new privacy regulations
- Making AI decisions more explainable
- Improving data quality and governance
- Strengthening cybersecurity measures
Practical steps for financial institutions
The experiences shared by HSBC and ING provide valuable insights for financial institutions at any stage of their analytics journey. Their successes and challenges outline a clear path forward.
Key steps for success
Financial institutions looking to enhance their analytics capabilities should :
- Start with strong foundations
- Invest in clear data governance frameworks
- Set data quality standards
- Build thorough documentation processes
- Create transparent data tracking
- Think strategically about AI implementation
- Focus on transformative rather than small changes
- Consider the full costs of AI projects
- Build solutions that can grow
- Balance innovation with risk management
- Invest in people and processes
- Develop internal analytics expertise
- Create clear paths for career growth
- Foster collaboration between technical and business teams
- Build a culture of data literacy
- Plan for scale
- Establish monitoring systems
- Create governance frameworks
- Develop standard approaches to model development
- Stay flexible for future regulatory changes
Learn more
Want to hear more insights from these industry leaders ? Watch the complete webinar recording on demand. You’ll learn :
- Detailed technical insights from both banks
- Extended Q&A with the speakers
- Additional case studies and examples
- Practical implementation advice
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Watch the on-demand webinar : Advancing analytics maturity.
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