Quais são as etapas essenciais para preparar seus dados de CRM para análise?

Beyond the immediate goals and questions, consider the long-term vision. What strategic objectives will your CRM data insights support? Aligning your analysis with broader business objectives ensures your efforts are not merely data-driven, but impact-driven.

This is such a big one because reports for the sake of reports is just a waste of time. There needs to be clear understanding of the outcomes the teams utilizing the CRM data are looking for and how that can be measured with data that can be captured in CRM. From there, you have to make sure that data has an effective and efficient way to be captured. Are the right fields in place on an account record? Are they easy for teams to keep them updated? Is anything redundant? It’s kind of like doing an organization project to make sure everything has a place so that a home can run more efficiently and it’s easy to find what you need.

The goal of any business apart from making a profit should be solving a problem. If a business can identify what problem(s) they are trying to solve, then it becomes easy to identify their goals and know what question they are trying to answer. Once a business is clear on the goals and WHYs, then they can identify what kind of data they require for any analysis.

Beginning a CRM project? Start by defining objectives. Often, clients are still exploring and understanding their needs. As specialist, we should lead and start the conversation with fundamental metrics like RFM, LTV, Cross-selling, and Churn and the data needed for theses metrics. Keeping it simple at the start lays the groundwork for powerful, focused CRM strategies that drive real results. #CRMStrategy #DataMetrics #BusinessObjectives #SimplicityInSuccess

Le plus difficile, c'est de faire le retro-engineering des indicateurs que vous souhaitez, pour que les données et paramétrages de votre outil CRM permettent de les produire. En dehors des indicateurs "classiques" et assez directs (volumes ou valeurs, par période de temps ou par équipe par exemple), tous les indicateurs avancés doivent être identifiés en amont et être intégrés dans la configuration pour que le système puisse les produire.

After defining your objectives and goals. You also need to understand how to relate to the CRM Is it a relational database or just a platform where you can download the document into excel. This step is very important

Go beyond basic checks! Leverage machine learning algorithms to identify patterns, anomalies, and hidden biases within your CRM data. This advanced analysis can reveal subtle data quality issues that might escape traditional methods, ensuring your foundation for analysis is robust and trustworthy.

Für ein effizientes datengetriebenes CRM sind hochwertige Datenpools von grundlegender Bedeutung. Bevor Unternehmen ihre gesammelten Daten in kundenfokussierten Prozessen nutzen, ist es entscheidend, die verfügbaren Daten selbst zu analysieren und ihre Qualität zu prüfen. Die heutige Datenerhebung erfolgt schnell und im Rahmen der gesetzlichen Möglichkeiten, wodurch Quantität in den meisten Fällen gewährleistet ist. Jedoch allein die Menge an Daten ist nicht ausreichend. Besonders wichtig ist die Qualität der Daten, vor allem wenn Künstliche Intelligenz (KI) oder Automatisierung im Einsatz sind. Die Zuverlässigkeit und Präzision der Daten sind entscheidend, um die Effektivität und Genauigkeit von CRM-Strategien zu gewährleisten.

Data standardization, deduplication, and enhancement are functions of normalization – a complex process post data acquisition. It's best to gather the data preformatted, singularly sourced, complete, and structured ideally for the type of analysis it is meant to be occupied for. When first acquired in the best form possible – everything in its place and a place for everything – any transformation necessary later on will be much easier to implement. For this, it's best to collect the minimal amount needed for the purpose in mind. More is less, since the more you gather un-normalized, the harder the labor necessary and greater the cost of standardizing that much more to produce useful information. This is all technical not Marketing work.

Don't just standardize, optimize! Consider implementing data enrichment techniques to enhance the value of your CRM data. This can involve integrating external data sources, such as demographics, firmographics, or social media insights, to create a richer customer profile.

Also, explore innovative data integration methods like real-time streaming APIs and cloud-based data lakes. These technologies enable seamless integration of diverse data sources, from customer interactions to IoT sensor readings, offering a real-time view of the customer journey.

It is great to have as much work automated as possible, and one of the ways to achieve it - is to do proper integration. For some tasks, there are stable and well-known services that you can rely on. At the same time, if you decide to utilize something new (for example in the beta-testing stage), it is important to always have a “Plan B” that ensures your organization keeps all the mandatory CRM flows in case these tools will be not stable or do not show the required result.

This is the sweet spot of a CRM. INTEGRATION. The more datapoints you can bring together, the better your changes of assessing the situational environment of your business and navigating to this changing world. Your CRM along is never sufficient!!! INTEGRATION is a crucial part of this. Once more, I will always recommend zoho crm for reasons like that. Very powerful environment too.

Transform data into a compelling narrative! Go beyond static visualizations and utilize interactive dashboards and storytelling techniques to engage your audience and communicate insights effectively. This can involve incorporating interactive elements like filters, drill-downs, and annotations, or weaving your findings into a clear and impactful narrative that resonates with your stakeholders.