What do you do if your customer analytics tools are too complex for most people in your company to use?

Making sure data is available and easy to understand is key to make sure to make decisions based on numbers, not intuition. Even more important to do it within CX. Some tips: implifying the interface and enhancing user experience through intuitive design and guided tutorials can empower employees across all levels to leverage insights effectively. Implemente a centralized data repository with user-friendly dashboards and automated reporting features ensures that valuable customer data is readily available to all stakeholders.

Simplify the interface and workflows of the analytics tools, provide comprehensive training sessions tailored to various skill levels, offer ongoing support and guidance, develop user-friendly documentation, and consider implementing intuitive data visualization tools to enhance accessibility and understanding across the organization.

Tools need to evolve along with the changing needs of the company/department. Set up an audit proces to evaluate all your analytics tools or find consulting firm that can do that. Ensure that your data analytics team is trained well to identify if the data you are capturing is and available to you is good or bad to make the right business decisions. Create a rubric to evaluate reliability of the data. Often times, 80% reliability is a good starting point. Another good practice is to ensure the right metrics are being measured to eliminate the noise in the tools. This can be achieved by getting all your stakeholders to agree on metrics that matter

In essence, simplifying it will enable more individuals to derive benefits from it. Embracing collaborative decision-making is consistently the optimal approach to engage and involve people.

Enabling products internally is key for teams to optimally use new tools. In my experience, hosting office hours, recorded trainings, sharing hot tips and a centralized FAQ page are all helpful ways for teams to learn a new tool.

Choose a suitable customer analytics tool based on your specific needs, features, usability, integration, scalability, support, and cost considerations. Train your team comprehensively on how to effectively use the chosen tool, including accessing, analyzing, and applying data, fostering exploration, collaboration, and continuous learning.

Finding the right tool is crucial, but so is training your team how to make the most of it. A lot of tools now include training on how to leverage it across different levels. For instance, if we're evaluating accessibility tools, there are training for teams who just need to understand basics, and then there are training for those designing or developing accessible solutions, which require more complex and detailed training. Another approach is training a few internal teams to be the SMEs to then retrain other teammates in the company.

Former son équipe est la base du management bienveillant. Une des meilleures méthodes également pour monter en compétence et valoriser les salariés. Leur montrer une montée en compétences, en responsabilité, est un levier fort (plus fort que les hausses de salaires???) pour conserver ses meilleurs éléments.

Focus on a few key metrics that align with your goals, such as customer satisfaction, retention, loyalty, or advocacy. Avoid overwhelming your team with irrelevant or excessive metrics. Clearly define and communicate the meaning and calculation of these metrics to ensure understanding. Visualize Your Data: Implement user-friendly dashboards and intuitive design to make data interpretation easier. Visual representations like charts and graphs can facilitate quick comprehension of complex insights. Share Your Insights: Encourage collaboration and knowledge-sharing by regularly communicating insights derived from the analytics tool. Use simple, digestible formats to convey important findings and actionable recommendations.

If people do not intuitively understand your team customer metrics you are doomed to fail. There is quite a lot of complexity within every company. The longer it takes to educate people the higher chances to lose them. Simplification of your metrics by for instance reducing their number (e.g. can you select max 3 KPI to assess customer experience?) will greatly help bringing people with you. Once people are "with you" you can move to the next step by either educating or even better co-creating a more sophisticated way of assessing your customer experience. Always and only if there will be the need to do so.

Too much information overload and tracking too many KPI’s can be difficult for the team to track and understand. The Mantra is to keep the things simple and straight. Rather than looking at the metrics that indirectly influence your targets, one should emphasize on directly impacting KPIs like Customer Lifetime value, NPS score etc. and more importantly the definition of these metrics should be same for all no matter the team/segment they are in.

Quoi de pire que les "vanity metrics"?? Vous savez, les données totalement futiles qui font principalement plaisir à votre égo? Quelles données sont réellement utiles pour votre entreprise? Pour améliorer votre offre, votre service client? Quelles données sont primordiales pour un calcul de votre productivité? De votre salary cost? Quels outils vous aident sur le prévisionnel, sur le calcul des possibilités de recruter ? Données utiles > Données plaisir

Imagine you're analyzing customer satisfaction scores over time. Instead of looking at a spreadsheet of numbers, the simplest visualization is to create a line graph that shows how satisfaction levels have changed month by month. Green indicates high satisfaction, yellow moderate, and red low. Immediately, you spot a trend where satisfaction dips during certain months, prompting you to investigate further. Now. you share this graph with your team during a meeting, and everyone instantly grasps the ups and downs without needing to dive into the raw data. By leveraging dashboards like this, you transform complex data into actionable insights that drive informed decision-making across your organization.

Visualize your data using charts, graphs, dashboards, or reports for clarity and understanding. Use colors, icons, and labels to highlight key insights and make the data more engaging. Visual representation helps in communicating findings, identifying patterns, and making data-driven decisions. Choose visualization techniques that best suit your data and audience to maximize impact and actionable insights.

In my experience data can be interpreted in numerous ways and require the simple, visual narrative catered to a specific set of people, goals, or topic. It’s a powerful tool and multi purposeful.

Visualizing your data is essential for making customer analytics more understandable and actionable. Use charts, graphs, dashboards, or reports to present data clearly and highlight key insights. Incorporate colors, icons, or labels to emphasize important findings and facilitate easy interpretation. By visualizing your data effectively, you can communicate insights, identify trends, and make informed, data-driven decisions.

Use Charts and Graphs: Utilize bar charts, line graphs, pie charts, or scatter plots to represent data in a visually appealing and easy-to-understand format. Create Dashboards: Develop interactive dashboards that allow users to explore data, drill down into details, and extract insights quickly. Color Coding: Use colors strategically to differentiate data categories, highlight trends, or emphasize important insights. Make sure to use a consistent color scheme for clarity. Icons and Symbols: Incorporate icons or symbols to represent specific data points or trends, making it easier for users to identify key information at a glance.

Here is an example: Let's say you've identified a trend in customer complaints related to shipping delays. You compile a presentation highlighting this trend, its impact on overall customer satisfaction, and potential solutions. During a company-wide meeting, you present your findings, emphasizing the importance of timely shipping for customer satisfaction. You use the right customer analytics insights to drive your point and conduct a brainstorming solution on action points and drive ownership for solutions from different departments like logistics, customer service, and sales. By making customer analytics accessible and relevant to everyone, you foster a culture of data-driven decision-making boosting overall customer experience.

With an overall CX strategic initiative in place, all employees and departments will know how to contribute to the success of these goals. The analytics, insights, metrics ... should be shared at all levels and all types of communications in the organization.

Remember to whom you're talking and what their goals are - if you or the dashboard you've built for them are giving them too much data (or in an overly-complex format), it's almost as bad as giving them too little. For most analytics conversations, you can just share the basic information and conclusions with your stakeholders - most of them don't care how the TV works; they just want to see the football game. Occasionally, you'll have a stakeholder who wants to get granular with you about tools and methods, and you can give them that option, but I find that the best client conversations happen when you answer the question that was asked without too much extra information.

Share customer analytics insights with the entire team and relevant stakeholders in your company. Avoid data silos and ensure accessibility of insights to all involved in customer experience. Use various channels like emails, newsletters, presentations, and meetings to share insights effectively. Encourage feedback and suggestions from your audience, demonstrating how insights can drive performance improvement across teams.

To maximize the impact of your customer analytics efforts, share insights with your entire team and stakeholders. Avoid keeping data siloed and ensure accessibility to relevant insights for all involved in shaping the customer experience. Utilize various channels like emails, newsletters, presentations, or meetings to disseminate insights effectively. Encourage feedback and suggestions to foster collaboration and demonstrate how insights can drive performance improvements across the organization.

Simplify, simplify, simplify! First, identify the most critical KPIs and metrics needed for your business. Then, explore user-friendly tools like Mixpanel or InMoment that offer intuitive dashboards and focus on those vital metrics. If necessary, invest in training or support to ensure your team can effectively utilize these tools. Remember, a tool is only as useful as its user's understanding. So, keep it simple and effective.

If the tool is too complex for the team to use that means the CX team was not included in the tool demo. Generally analytics tools are used by the data team and they present the data in a meaningful & understandable manner. Hence you need to: 1. Understand the pain points in using the tool 2. Hire someone from analytics to present the data in a meaningful manner 3. Side by side train the team in tool usage, if not all maybe some members who may be more comfortable in learning and adapting 4. If possible change the tool and this time include all the teams in demos to gauze their comfort and understanding

If genuinely customer-centric, you would care as deeply for your colleagues' needs as your customers. When your tools are too complex, you miss some elements in learning the needs of your colleagues. It might even be a sign that your CX in itself misses some essentials. If you are not serving the needs of your colleagues correctly, how likely is it that you are serving your customers' needs? Use the red flags to calibrate and to do a better job internally and externally.

Si las herramientas de análisis de clientes son demasiado complejas para la mayoría en mi empresa, ofrecería capacitación adicional, y buscaría alternativas más intuitivas. También establecería un equipo de asistencia técnica y consideraría externalizar el análisis si persiste la complejidad. Después de todo el Employee Experience también hace parte de la estrategia.

Customer Journey Mapping: Use customer journey mapping to pinpoint key touchpoints where metrics can be applied effectively. This helps in understanding the customer experience comprehensively and targeting improvements strategically. Benchmarking: Compare your metrics against industry standards or competitors' performance to gain insights into your performance relative to others and identify areas for improvement. Feedback Integration: Incorporate customer feedback into your metrics strategy to complement quantitative data with qualitative insights, leading to a more nuanced understanding of customer perceptions and behaviors.