Types of Business Data Analytics Tools

The data seed discoveries, which eventually create engaging strategies. Recently, Google claimed that its Sycamore processor can process a calculation in less than three and a half minute. A classic computer could take 10,000 years to complete this very target. This news in the journal Nature circulated out of the blues, stirring the world.

The data-driven strategies, certainly, bear intelligence that ensures computing profit out of it. In the nutshell, breakthroughs are the upshots of data analytics. Certain tools, like Google Analytics, Splunk and Salesforce, are exponential to collect and process data for analytics and hence, business intelligence.

Here are some important tools that can help you manage a business smoothly:

  • IT log data management tool:

A log determines an automatically generated document, carrying time-stamps of events relevant to a particular system. Almost all software applications and systems produce log files in the background. In businesses, the data management tool provides with the IT admins to automatically fetch log data from tablets, mobile phones, systems and various networks.

The entrepreneur creates a unique sense and models through computer-generated logs, which support in reviewing daily logs, erroneous links, anomalies and suspicious activities or attempts. In essence, these logs ground up real-time statistics to analyse & introduce breakthroughs.

A few examples of these tools:

  • Papertrail (Cloud-Based)
  • Loggly
  • Logentries
  • Go Access
  • Logz.io
  • Customer data platform:

The customers’ data is a key to dig out their behavior (buying criteria and purchase patterns), which eventually merges into predictive analysis. It often proves a breakthrough, boosting online visibility, leads and conversions.  The customer data platforms, such as AWS, can help the entrepreneur to tap his customers for blueprinting prospective marketing strategies.

Now-a-days, the most pervasive trend of customer analysis is through digital data analytics tools.

A few examples of the customer data platform:

  • Evergage
  • Optimove
  • Exponea
  • Listrak
  • FullContact APIs

One should select the best one while keeping into account if or not it extracts these databases:

  1. Interest Data: By churning interest, the business doers come across what ways the customers can be delighted. In short, it helps in:
  2. Understanding users’ interest
  3. Getting clues to refine products according to
    users’ preference
  4. Coming across what sources the user likes to
    access your product/services
  5. Knowing the most preferable payment platform
  6. Engagement Data: Engagement evaluates the action
    of customers while being on the website or the app.
  7. Activation Metrics
  8. Number of daily subscribers
  9. Count of successful signups/day
  10. Count of users who activated location
  11. Count of signups/day that did not complete
  12. Retention Metrics
  13. Daily active users
  14. Monthly active users
  15. Session/ daily active user
  16. Percentage of monthly users who become daily
    users
  17. Retention rate
  18. Churn rate
  19. Conversion Metrics
  20. Average revenue per user
  21. Average revenue per paying user
  22. Average revenue per daily active user
  23. Average check
  24. Payer conversion rate
  25. Lifetime user
  26. Churned payer
  • Data management platform:

Data management is complex process. But, it is extremely sensitive at the same time as well. The entrepreneurs accumulate facts and figures flowing from the first party, second party and third party sources. Subsequently, the pan data are pushed into the funnel where they achieve   an organized structure. In short, the database is processed into the comprehensive information. Certainly, this information proves pivotal in accelerating to groundbreaking decisions/ strategies.

A few examples of Data Management tools:

  • AWS
  • Panoply
  • Google Cloud
  • Profisee
  • SAP NetWeaver

Components of data management:

  1. Data Warehousing (Where and how to archive data for sharing later)
  2. Data Modeling (to comprehend and derive intelligent patterns)
  3. Defining privacy policy/ copyright policy/ intellectual policy
  4. Documentation (Defining metadata)
  5. Defining types & formatting (Creating hierarchy of files & directories)
  6. Organising files (for tracking easily)
  7. Data encryption & security
  8. Backups & storage
  • Customer relation management tools:

Like customer management, the customer relation management can prove a game turner. This is why various businessmen deploy CRMs to eventually leap on to the breakthroughs. It could also identify how customers get engaged.

A few examples of customer management tools:

  • Zoho CRM
  • Hootsuite
  • Kissmetrics
  • Alteryx
  • Salesforce

Customer relation management analytics:

  1. Grouping customers
  2. Analysing profitability
  3. Evaluating customer value
  4. Tracking and measuring escalation arising from problems with a specific product or service
  5. Drafting predictive models
  6. Personalizing marketing campaigns
  • Social media analytics tools:

The social media analytics tool, like Facebook Insights, helps to extract perceptions, as what customers like and dislike. Like web analytics tools, these tools pull intelligence about customer behavior, prospects, sales and conversions.

A few examples of social media analytics are:

  • Brandwatch
  • BrandMentions
  • Meltwater
  • Reputology
  • Tapinfluence