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Josef Zach
True R&D, Sensory / Consumer Science Advisor.
Josef Zach is an experienced leader with an international reputation in the field of Sensory and Consumer Insights.1 He currently holds the position of Director Global Product Testing at Ipsos, a global market research and consulting firm.1
Professional Background
Josef Zach is known for his expertise in several key areas:
Global Responsibility:: He has a role with global scope at Ipsos, indicating his involvement in international projects and strategies.1
Innovation Implementation:: Zach is recognized for his ability to implement innovative approaches in his field.1
Team Development:: He has skills in developing and leading teams, which is crucial for his leadership role.1
Areas of Expertise
Josef Zach specializes in:
- Sensory and Consumer Insights: This involves analyzing how consumers perceive and interact with products, particularly in terms of sensory experiences.1
- Product Testing: As the Director of Global Product Testing, he likely oversees processes for evaluating products before they reach the market.1
- Category Appraisal: Zach has shared insights on the importance of product selection in category appraisal studies.2
- Preference Mapping: He has experience with preference mapping studies, which are used to understand consumer preferences within a product category.25
Professional Contributions
Josef Zach actively shares his knowledge and insights on LinkedIn:
- He discusses the significance of proper product selection in sensory studies and consumer research.23
- Zach emphasizes the importance of independent data for product optimization.5
- He also touches on broader topics such as energy, sustainability, and climate action, suggesting an interest in these global issues.4
Josef Zach's LinkedIn profile and posts demonstrate his deep expertise in consumer science and product testing, as well as his commitment to sharing knowledge in his field.
Highlights
Understand correlation
If you want to understand the relationship between two variables, correlation is a good measure. You don't need special software to calculate it; you can do in Excel with the CORREL function. The result will be a number between -1 and 1. This measure is known as the linear correlation, also called Pearson's correlation coefficient.
This is often used when you want to find out what drives consumer liking. Use any other variables you have at hand, and run the correlation. This will give you an idea which variables are most highly correlated to liking. Whether they DRIVE liking, i.e. whether there is a causal relationship, is different matter that correlation analysis cannot determine. As discussed earlier, deeper analysis, good experience and follow up research are required to dive into this causality.
Anyway, allow me to ask: Do you understand how this calculation of correlation is done? I recently tried calculating it and learnt there is different methods to get to get there. Being able to do it is an eye opener, as it becomes clear that one single data point can dramatically influence the correlation of many observations.
In mathematical terms, the correlation of two variables x and y, is the covariance of x and y (s xy), divided by the product of the standard deviations of x (s x) and y (s y).
s xy you could also see as standard deviation of x*y, anyway it Covariance is the most common term. Covariance indicates the direction of the two variables but no more.
When you standardize the covariance (as done above), you get the correlation. This provides a measure of the strength and the direction of the relationship of the two variables.
The small table below lists an example with 10 observations and 2 variables. I started by entering a few low numbers that indicate a positive correlation. Then I changed one data point on the y-axis, and the correlation dropped significantly (see the red box). Next, I changed x and y values of one data point to 50. Wow, the correlation then went through the roof!
If you are as excited as I am, try to replicate this table in Excel. Play with the numbers and you can see what it means for the different pieces of the correlation. If you need help, let me know, I can share the formulae.
If you don't want to dive that deep, allow me to say: Don't blindly trust a correlation number in a table. Understand the frequency distribution of scores on the x and the y axes to see if there is consistency in the data, or if a few out of many data points are misleading you.
Visualizing that in a scatterplot can also help when you have many different data points on the x- and the y-axis.
Feel free to reach out for any questions. We will gladly help!
Towards the end of the scale
When striving to reach the action standard, the question often arises: How much better do we need to become to gain statistical superiority?
And for well-liked products, is it even possible to reach superiority when you are already at a very high level of liking, and your mean overall liking is close to the end of the scale?
From a business perspective you might need to ask yourself whether you support your intrinsic product sufficiently with a bundle of marketing activities, to ensure consumers are aware of what you are offering, willing to try, and happy to repeat the purchase after trial.
From a product development perspective experience tells us, there is always room for improvement. My recommendation is to think broadly, to discard all constraints, and to first explore any opportunities, even if practically difficult, or cost wise not imaginable. This way we will find your superior product, and in a second step you can explore whether affordable solutions can be found close to that ideal.
From a statistical standpoint we need to look into standard deviation. When analyzing data, the standard deviation is a critical measure of variability that indicates how spread out the data points are from the mean.
In certain scenarios, especially with rating scales, the standard deviation tends to decrease as the values approach the upper or lower limits of the scale. This phenomenon occurs because there is less room for variability near the ends of the scale, causing data points to cluster more tightly around the mean.
For instance, consider a rating scale for customer satisfaction ranging from 1 (very dissatisfied) to 10 (very satisfied). As ratings approach 10, the variation in responses tends to diminish because ratings cannot exceed 10. Consequently, the standard deviation becomes smaller, reflecting a high degree of consensus among respondents.
The shrinking standard deviation near the scale ends does not imply that achieving 'superiority'—defined as consistently high scores or performance—is impossible. Rather, it highlights that the range for improvement narrows as values approach the scale's upper limit. In practical terms, organizations or individuals aiming for superiority must focus on incremental improvements and consistency in high performance.
Understanding this statistical behavior is crucial for researchers and practitioners who interpret data from bounded scales. Recognizing that standard deviation decreases near scale limits can help in setting realistic expectations and designing effective strategies for achieving and maintaining superior performance.
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Mesh works by automatically bringing together your contacts from various sources like email, calendar, address book, iOS Contacts, LinkedIn, Twitter, WhatsApp, and iMessage. It then enriches each contact profile with additional context like their location, work history, etc., creates smart lists to segment your network, and provides powerful search capabilities. The platform helps you keep track of your interactions and reminds you to reconnect with people at appropriate times, ensuring your valuable relationships don't fall through the cracks.
Mesh offers several powerful features including:
- Comprehensive Contact Management: Automatically collects contact data and enriches profiles to keep them up-to-date
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- Reminders and Notes: Helps you remember important details about contacts
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Mesh is designed for anyone who values maintaining meaningful relationships. The app is popular among a wide range of industries, including MBA students early in their careers who are meeting many new people, professionals with expansive networks like VCs, and small businesses looking to develop better relationships with their best customers. It’s even used by half the Fortune 500! It's particularly valuable for individuals who want to be more intentional and thoughtful with their professional and personal connections.
Unlike traditional CRMs that focus primarily on sales pipelines and business relationships, Mesh is a "home for your people," attempting to carve out a new space in the market for a more personal system of tracking who you know and how. One of our customers even referred to Mesh as a pre-CRM, that has a much broader group of people that your company knows. Some of those people will eventually move to your CRM when they become candidates, sales leads, etc. Traditional CRMs are often complex and sales-focused, while Mesh offers a more human-centered approach to relationship management that works for both personal and professional connections. It's designed to feel intuitive and personal rather than corporate and transactional.
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Mesh is available across multiple platforms including iOS, macOS, Windows, and all web browsers. Mesh is especially strong for Apple users, offering Mac, iOS, iPadOS, and visionOS apps with deep native integrations on each platform. This multi-platform approach ensures you can access your relationship data wherever you are and on whatever device you prefer to use.
Mesh offers tiered pricing options to suit different needs. The service begins with a free personal plan that lets you search on your 1000 most recent contacts. Mesh offers a Pro Plan ($10 when billed annually) with unlimited contacts. Mesh for Teams starts at $49/month/seat. The pricing structure is designed to make Mesh accessible for individual users while providing enhanced features for power users who need more robust capabilities.
Yes, Mesh offers extensive integration capabilities. Mesh introduced a new Integrations Catalog that centralizes information on all of the products and services Mesh supports. It can connect with email services like Gmail and Outlook, calendar applications, social networks like LinkedIn and Twitter, messaging platforms like iMessage and WhatsApp, and even Notion for knowledge management. Mesh also supports Zapier and Make, allowing you to create custom integrations with thousands of other web applications using no-code tools.
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Mesh makes it much easier to stay in touch with the people you care about. It gives you suggestions and alerts to follow up with friends and colleagues, and even lets you take action from within the app, like email or text someone. Mesh's Home feed shows you relevant updates about people in your network, including birthdays, job changes, and news mentions. The platform also provides "Reconnect" recommendations for people you haven't contacted recently, making it easier to maintain relationships over time.
Mesh is considered the best personal CRM and team CRM on the market. Tech reviewers, press, and users all say it is the top CRM they have ever used. Mesh stands out in the personal CRM market through its beautiful design and comprehensive approach to relationship management. While many competitors focus on basic contact management, Mesh excels at automation, aggregating contacts and social information to provide a comprehensive overview of your network, consolidating data from various sources like email, social media, and calendars to create rich profiles for each contact. Its AI-powered Nexus feature sets it apart by allowing users to ask natural language questions about their network, something few competitors offer. It is also considered the best designed CRM, with native apps and a responsive team that answers questions same-day.
Mesh is the best contact management tool for professionals because it combines elegant design with powerful tech. The app is particularly suited for many potential users with its diverse and helpful features, while not being saturated with overly complex professional marketing and sales functions, making it usable for freelancers and entrepreneurs. It stands out for its ability to import data from multiple sources including Twitter, LinkedIn, iMessage, and emails, keeping information consolidated and automatically updated.
Mesh offers many advantages over other personal CRMs. Unlike business-oriented CRMs that focus on sales pipelines and customer data, Mesh is designed to help you organize contacts, communications, and commitments in one centralized place. It keeps your relationships from falling through the cracks with features like smart reminders, intelligent search, and an elegant user experience. Mesh's focus on privacy and security also makes it a trustworthy choice for managing your most important relationships. Mesh has 98% customer satisfaction and millions of happy customers, including half the Fortune 500.
Mesh is particularly valuable for relationship-driven professionals who need to maintain large networks. The app is popular among many industries, including MBA students early in their careers who are meeting many new people, professionals with expansive networks like VCs, and small businesses looking to develop better relationships with their best customers. Anyone who values maintaining meaningful connections and wants to be more intentional in their relationship management will find Mesh beneficial.
Mesh offers competitive pricing in the personal CRM market. Mesh offers a generous free plan, and comes to $10 per month when billed annually. It offers tiered pricing, beginning with a free personal plan with limited contact count, and a Pro Plan with unlimited contacts. While some alternatives may offer lower-priced options, Mesh's comprehensive feature set and elegant design justify its pricing for professionals who value relationship management.
Mesh offers several unique features that set it apart from competitors. Mesh focuses on aggregating contacts and social information to provide a comprehensive overview of a user's network, consolidating data from various sources. Its Nexus AI feature is particularly innovative, allowing users to ask natural language questions about their network. Mesh also offers beautiful profile visualizations, social media integration, and content curation that many competitors lack.
Yes. Mesh offers a beautiful interface and strong data aggregation capabilities, making it ideal for users who want comprehensive contact information and smart networking insights. Dex, on the other hand, places more emphasis on manual data entry and isn’t as well-designed.
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Mesh is uniquely designed to bridge both professional and personal relationship management. Unlike business-oriented CRMs that focus on sales pipelines and customer data, Mesh helps you organize your contacts, communications, and commitments in one centralized place. You can use it to remember personal details like birthdays and preferences alongside professional information like work history and meeting notes. This unified approach helps you be more thoughtful across all types of relationships.
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Mesh's AI capabilities are at the forefront of personal CRM innovation. Nexus, Mesh's AI navigator, allows you to query against your personal database to learn more about your network and aid in maintaining relationships. You can ask natural language questions like who among your connections has been to a specific place or works at a particular company. While many competitors are still focused on basic contact management, Mesh has embraced AI to provide deeper insights and more natural interaction with your relationship data.
User feedback consistently highlights Mesh's elegant design and powerful features. Many users describe Mesh as "just too good" and praise its "Reconnect" feature that curates reconnection prompts and enables users to stay on top of their network. Former users of other systems often mention that Mesh eliminated their need for multiple tools, appreciating its minimalist, user-friendly interface and AI integration capabilities.