What are some common business analytics tools and how can you use them to improve customer satisfaction?

For example (but not explicit recommendations as you need to pick): 1. Google Analytics to track website user behaviour to improve online customer experiences. 2. Tableau to visualize customer data for better understanding of preferences and trends. 3. SAS analytics to analyse large datasets to identify customer needs and forecast trends. 4. Microsoft Power BI to create interactive reports to understand customer interactions and improve services. 5.CRM Systems (like Salesforce) to help manage customer relationships and personalize interactions. 6. Hootsuite or Sprout Social to help you monitor social media for customer feedback . 7. SurveyMonkey to help you conduct customer surveys to gather direct feedback and refine your services.

Business analytics is a process to derive meaningful insights or business value from historical data, The tool you consider and choose should compete and win with BA projects, Typically four steps involves in BA from Data to Business value. 1. Data Acquisition 2. Data preparation. 3. Application of Appropriate algorithm. 4. Visualisation and Reporting. I would heavily recommend one of high impact tool Statistica, Gartner named as a leader in Data Science, ML and AI category. Let me also mention few of the High impact application of BA such as. - Market/Customer segmentation. -Business forecasting. - Market Basket Analysis. -Consumer psychology mapping. -Employee retention model. However majority of Business problems can solve using BA.

Especially if your organization relies heavily on much of the Microsoft stack, Power BI is it should likely be a cornerstone of your data services or analytics team. I’ve seen success first hand from data enablement, operational KPI creation, as well as overall governance monitoring in EDW integration. Especially when first mining new or underutilized data sources, Power BI is a fantastic tool for AdHoc and POC analysis which then can be transformed to enterprise wide impactful insights and actionable storytelling to foster success in not only organizational goals, but even month to month A/B testing of CRM strategies.

The entire Qlik suite can be utilised for data warehousing, integration, analysing, reporting and so much more. Microsoft power bi and fabric and Alyetyx are other end to end D&A tools. If you are looking at your business intelligence and want to unravel your company data complexity and unlock its potential to drive business outcomes give me a shout ?? There is some great recent customer success stories on my LinkedIn go have a look ?? I can put you in touch with one of Cybit’s Data & Analytics Consultants for a free D&A Health Check which looks at your data estate, business challenges and provides an output report for recommendations to make your business more data driven. ?? ??

Google Analytics - Brings data from website to your dashboard Zapier - Is an intermediate tool connecting your dashboard with a CRM or Analytics tool Power BI- is a final tool which connects your BI tool to the database (but it’s not a collection tool) Among those mentioned above only Google Analytics is a pure data collection tool

This one of the most important steps in the entire analysis and you need to use proper tools to allow you discover insights from your data. Tools and methods are playing a big part here and having the wrong one in place might compromise the end result.

Python - For the popularity and flexibility R - for straightforward stat tasks SAS - old but gold, nice tool still in use in some of important organizations but ultimately i am hearing less and less about it Qlik - I prefer Power BI or Tableau. Qlik is so behind (according to the Gartner)

Along with these tools, Looker can be a very good starting point for very small datasets. It's basic but helpful enough to visualise a dataset on a Google sheet or csv file

Power BI: Enables data visualization and interactive dashboards, aiding in understanding customer trends. Tableau: Offers advanced analytics and visualization tools for data exploration and interpretation. By using above tools, one can analyze customer data, their behaviour and feedbacks through apps and websites, to identify segments with specific needs or their preferences.

The master step required to find any kind of insights or trends is the data analysis. For Data Analysis part, rather than using tableau or excel directly, I recommend doing all the logic making part in SQL (BigQuery by Google Cloud Platform is preferred due to its tremendous speed). As a next step, you can seamlessly integrate your SQL queries with Tableau for better Visualization of insights and also for automations.

What makes CSAT interesting is that it frequently involves two different analytical worlds: Market Research and Data Science. List processing from the data team extracts names and data from large databases, requiring big data tools like SQL and Python or embedded corporate systems tools. Market Research then takes the lists and surveys them, using firms like Qualtrics. Then satisfaction survey results are analyzed by statisticians and/or data scientists, frequently using smaller scale tools like Excel and IBM SPSS, as well as R and Python.

This step is required for complex data sets and for more accurate predictions. For Data Mining and Machine Learning, one can use Python, which has abundant set of easily available libraries and multiple resources to refer to. On top of it, we can use multiple tools including Scikit-learn and Tensorflow, through which we can implement machine learning models that can predict the outcomes, or to classify user segments based on their traits or historical behavior.

AI can help analyze unstructured data like customer feedback and reviews to extract insights, do Sentiment Analysis, etc. to help businesses better understand customer sentiment and preferences.

Based on my Fortune 500 experience: Data quality and governance is the most important step in all of analytics and should certainly not be last. As the old saying goes “junk in and junk out”. As business professionals we should know well that we must address inputs to a process before the outcomes, and the first input to analytics is the data. Use Informatica when you can, Tableau is the better of the two major visualization tools and most importantly, set up a governing body of some kind for your most valuable KPIs to have oversight of their data glossary definitions.

Data quality is becoming the trend nowadays. It’s also because of the KYD (Know Your Data) which is a concept next to KYC. Nowadays, businesses should make sure of the quality of the data. Dataiku and Alteryx are famous tools for it

For me the go-to tool is Tableau. The point and click interface allows it to be simple for simple use cases and advanced for those who have those skills. I like how it can expand based on the needs. The stories feature allows one to present compelling narratives from complex data and what I have noticed is that during a presentation if questions are asked one does not need to say the typical “let me get back to you on that”, questions can be answered immediately and the train of thought and discussion is richer.

I like Tableau better as well, but there is a fairly steep initial learning curve. Once you get past that though, there are amazing things you can do not possible in PowerBI.

GIVE A POWER TO AN END USER! This part is when your end user should have that Aha! Moment. If you want to make the end user adjust the data then publish Dashboards on Power BI or Tableu. Or if you are doing a presentation. Use PowerPoint. Canva is a handy tool however it’s not professional enough

Once all the prior steps are done, the last but the most important part for stakeholders is storytelling and presenting the actionable data in form of charts/graphs/summaries. For this purpose alone, we can use tools such as Powerpoint where you can brief on the outcomes of all findings and the future initiatives inspired from the data insights. You can also use Tableau directly in some situations where not much of a fancy presentation is required and when you need to quickly summarize the findings.

SAS with built in rich analytics is the go to tool for me. These days senior leaders need the most accurate information available in real time and SAS with the simple UI but powerful features is the storytelling tool I would recommend

In my opinion, the must important thing it’s not fall in love with a specific tool, such as Power BI, Tableau, DataBricks, Snowflake, KNIME analytics and etc. With all the technology’s that are coming, specifically Chat GPT, Google Bard and all the new IA’s be open to learn is the key.

Regardless to the task there is no a specific tool that should be used for a certain task. Indeed some of the service providers are giving the possibility to use several tools on the platform. For instance DataBricks gives you opportunity to use either R or Python on it

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I would recommend Power BI, Tableau, or Qlik as they are powerful data analytics tools for various reasons such as ease of use, robust data connectivity, advanced data visualization, scalability, in-memory processing, data security, community and support. These tools can provide a holistic view of the retail business, enabling data-driven decisions that positively impact customer satisfaction through optimized inventory, proactive issue resolution, and personalized customer experiences.