Top 20 Data Analysis Tools
By: Maryna Sharapa
Tags: Owox Bi, Data, Tools, Marketing, Data Analysis

Top 20 Data Analysis Tools

In this article, we review 20 widely used data analysis tools and help you choose the most suitable one according to your needs. Maryna Sharapa Follow Dec 24, 2020 · 15 min read

Building a good marketing strategy begins with data analysis. After all, you can’t improve anything without assessing its starting point. Luckily, you don’t have to do it manually — there are a bunch of specialized tools that can help you automate data analysis to save time.

What is data analysis?

In marketing, data analysis is the process of organizing, explaining, and interpreting data to answer questions regarding a marketing strategy, resolve issues with that strategy, and multiply its advantages. You might ask the following questions as the first part of data analysis:

What’s the most effective advertising channel?

How many unique visitors does my website have on average per day, week, and month?

What channels should we focus on to raise revenue?

Data analysis is a must for marketers. It’s how they can avoid guesswork and see what areas of their marketing performance require special attention. Marketers can use data analysis to uncover trends, patterns, and valuable insights in order to adjust advertising campaigns and get more revenue.

By analyzing data correctly, you can achieve the following marketing goals:

Decrease ad spending. Find ineffective campaigns, stop investing in them, and focus on revenue-generating channels. Increase revenue from visitors. Predict LTV (customer lifetime value) and the conversion probability; offer products visitors really need by enhancing the level of personalization. Make data-driven decisions. Get high-quality data to have a solid basis for making timely decisions and be sure of your next steps.

Data analysis tools for marketing differ in their level of detail and methods of interpretation. Generally, they focus on gathering, analyzing, or visualizing data. Still, the number of options on the market is quite large, and it’s not that simple to find the perfect tool. To help you narrow down your list, we suggest things you should consider when selecting a data analysis tool.

How should I analyze data?

The primary goal of data analysis is to find meaning in data and use this meaning to improve your marketing strategy.

Data analysis consists of the following steps:

Define your goal. Figure out your expectations, specify the questions you’d like to answer with the help of data analysis, and determine which data you need to collect (data on advertising campaigns, visitors, orders, email openings, etc.). Collect data. Collect and merge data from different sources, then clean, arrange, and organize it. Ensure data quality. Make sure your data doesn’t have errors, gaps, or unnecessary parts. If it does, further interpretation won’t be trustworthy. Analyze data and interpret results. Build dashboards, reports, or charts and correlate them with your primary questions and expectations. Act on data. Based on your interpretation of the data, take actions that will improve your performance — reallocate your budget, adjust bids, create new audience segments, or turn off ineffective campaigns. Repeat the cycle to analyze how data changes over time.

Manually collecting, cleaning, and arranging data takes a lot of time, and the probability of human mistakes is high. Poor data quality can result in losing 21% of your marketing budget, and according to Gartner, businesses all over the world lose an average of $15 million per year for this reason. You can spend hours finding errors in piles of data with no guarantee that the results will be precise. To save time and make sure your data is accurate, you need to perform automated analysis using specialized tools.

Before selecting a tool, narrow down the list of possible options by defining:

the types of data you want to analyze

of data you want to analyze the goal you’d like to achieve with the help of analysis

you’d like to achieve with the help of analysis the level of detail you would like in your analysis

Now let’s take a look at twenty of the most popular data analysis tools.

Top 20 data analysis tools

We’ve prepared a list of the best tools to collect, analyze, and visualize marketing data. For each tool, we describe how it works and what its key characteristics are.

Tools to collect and analyze data

1. Google Analytics

Google Analytics is the most popular analytics service. It collects information from three sources: users’ HTTP requests, cookies, and data on browsers/operating systems using a Google Analytics Tracking Code. Once data is collected, it goes to Google Analytics servers as a list of parameters. Google Analytics then analyzes these parameters and creates reports you can find in your Google Analytics account.

Key characteristics:

Limits on data collection — can collect up to 10 million hits per month per property with the free version; to collect more, upgrade to Google Analytics 360 or use another tool

No data from CRM and non-Google services unless you import it manually

Data is processed within 24 to 48 hours

Google Analytics is free to use, but if you operate with high data volumes, you should upgrade to Google Analytics 360 — which starts at $150,000 per year.

2. Mixpanel

Mixpanel is a user analytics tool that allows you to track user behavior. You can do this by sending data from your server to Mixpanel, which will analyze it in real time. Mixpanel uses an event-based, user-centric model to analyze user actions with your product. The Mixpanel data model is built on the following key variables:

event — a user action on a website

property — a detail about an event

user profile — a collection of information about an individual user

Key characteristics:

Have to create a tracking plan with your business goals before collecting data

Has a custom datastore with its own structure that’s different from other similar tools

Limits on how much data you can collect — only 2,000 properties per user profile

Mixpanel offers a free plan for up to 100,000 monthly tracked users, and pricing for plans with unlimited reporting starts at $17 a month.

3. Kissmetrics

Kissmetrics is a business intelligence platform that allows you to analyze users’ behavior on your website, categorize audiences, and store data in one centralized platform. The Kissmetrics JavaScript Library automatically tracks several events: visited site, form fields, ad campaign hit, search engine hit, and page view. It also allows you to track customer profiles, reports, events, and campaigns as well as users’ anonymous activity before they sign up.

Key characteristics:

Can track data in real time with the Kissmetrics Live feature

Limited integration options, and it’s not possible to integrate Kissmetrics with Google products

Suitable for small and medium-sized SaaS and ecommerce businesses

Pricing starts at $299 per month.

4. Weborama

Weborama is a marketing technology company that provides behavioral targeting services and advertising analytics based on a semantic analysis engine. With the Weborama BigFish semantic AI platform, you can analyze website conversations, user behavior, and consumer insights. With the Weborama BigSea dataset, you can create a consumer database and build a relevant digital behavior score for each user.

Key characteristics:

Allows you to unify CRM and behavioral data and build a predictive model of user behavior

Performs direct marketing self-activation of audiences that have a high churn risk

Need a separate tool to collect your data before uploading it to Weborama for further analysis

Pricing for Weborama services isn’t available on the official website. You must contact a representative to obtain current pricing.

5. OWOX BI

OWOX BI is an all-in-one marketing analytics platform that automatically collects data from multiple online and offline sources in one place — such as Google Analytics or Google BigQuery — where marketers and analysts can work with it.

OWOX BI merges, cleans, and organizes data collected from ad services, websites, Google Analytics, CRMs, offline stores, and other sources. You can then use it to create reports based on this data from templates or build your own reports with custom metrics to measure what works best in your marketing. One of the big benefits of OWOX BI is that to do this, you don’t need to code or know SQL — you can build any report you want using natural language in a simple report builder.

Key characteristics:

Collects data in the same structure as Google Analytics and monitors data quality

Can integrate with other marketing tools such as Google Analytics and Google BigQuery and can import your calculations to visualization services or BI tools — for example, Google Sheets, Looker, Tableau, Power BI, and Data Studio

No limits on collected data, and it’s always unsampled and processed in real time

Offers its own data-driven ML funnel based attribution model that evaluates how your marketing channels influence one another and conversions

You can start using OWOX BI with a free plan. Paid plans start from $42 a month, and you can request a plan to meet your specific needs.

6. Datorama

Datorama is an AI-powered business intelligence and analytics platform with built-in reporting, insights, and automated predictions on goal completion. It collects and merges marketing data in one centralized platform, analyzes data across different channels and campaigns, and builds reports based on the results.

Key characteristics:

Suitable for B2B marketers and enterprises

Allows for cross-platform management: adjust campaigns in Google, Facebook, and other tools connected to Datorama

Plans are expensive and only billed annually

Pricing starts at $3,000 per month, billed annually.

7. Supermetrics

Supermetrics is a cloud-based ETL platform that collects and analyzes your marketing data using APIs and sends it to storage or to a visualization, reporting, or BI tool of your choice. Supermetrics allows you to automate reporting and transfer data where you want it.

Key characteristics:

Doesn’t offer data quality monitoring and attribution reporting

Can connect Supermetrics to Google Data Studio, which is convenient

Offers multiple integrations, including with data sources such as Google Analytics and Google Ads

Pricing starts at $39 a month and depends on the integrations and features you select.

8. Funnel

Funnel is an ETL platform that allows you to collect data and automatically process it by cleaning, mapping, and grouping it. Based on this processed data, you can create reports and dashboards with key metrics you select and send the collected data to a data warehouse, Google Data Studio, Looker, or some other tool (Funnel offers about 500 integrations).

Key characteristics:

Doesn’t support dynamic UTM parameters or streaming user data from a website

No data quality monitoring or attribution reporting

Gathers data in its own data warehouse, from which you can transfer it wherever you need to store it

Can connect Funnel to Google Data Studio, which is convenient

Pricing starts at €499 per month.

9. Improvado

Improvado is a cloud-based ETL platform that collects data from different sources and arranges it using a REST API. Next, it analyzes data by merging tables, making calculations, and modifying the data structure. Interpreted data then goes either to external data storage (Google BigQuery, Redshift, PostgreSQL, etc.) or to the internal Improvado database.

Key characteristics:

Initial data collection takes about 24 hours, after which data is refreshed twice a day

Can use Improvado with other marketing tools — for example, Google Analytics and Salesforce

No free trial period

Doesn’t collect data on user behavior and doesn’t perform cohort analysis

Pricing for data analysis in Improvado is determined on a case by case basis.

10. AppsFlyer

AppsFlyer is a mobile marketing analytics tool that allows you to create dynamic cohort, retention, and raw data reports as well as custom dashboards and live alerts. With AppsFlyer, you can track the performance of your paid mobile media sources and their organic activity in real time.

Key characteristics:

Offers a secure storage locker hosted on Amazon S3 to ensure data security

Offers localized language, time zone, and currency support

To collect and analyze data from your website, ad services, CRM, and offline stores, you should consider using another tool such as OWOX BI

You can start with a free account, then pay from $6 per conversion as your business grows.

11. Adobe Analytics

Adobe Analytics allows you to merge and analyze data on customer journeys in real time based on online and offline sources. Adobe Analytics offers various types of analysis, such as ad hoc (custom), cohort, and flow analysis, which allows you to track the most important aspects of the user journey.

Key characteristics:

Can set up alerts to detect anomalies using statistical modeling and machine learning

Can integrate with other tools using APIs or a drag-and-drop UI

No free trial available

Even though you can compare plan pricing for Adobe Analytics — Select, Prime, and Ultimate — you still must contact an Adobe representative to get the exact price for your company.

12. Fivetran

Fivetran is an automated data integration and analytics ETL tool that allows you to merge data from multiple sources in one platform.

Key characteristics:

Thanks to log-based replication of databases, offers a capture deletes feature to analyze information that may no longer exist in the data source system

Doesn’t store data but loads it into a data warehouse you select

Offers history mode to analyze data from a particular point in time or track its changes over time, but this option isn’t available for all data connectors

Fivetran pricing is consumption-based and starts at $1 per credit. This means that each month, Fivetran calculates how many monthly active rows (MARs) you used during the month and what the price is for the month. Alternatively, you can purchase a certain number of credits in advance.

Data visualization tools

13. Google Data Studio

Perhaps the most popular data visualization tool is Google Data Studio — a visualization and reporting tool that allows you to set up a data connector to collect, filter, and compare data, set up automated interactive dashboards, and share reports with your colleagues. Also, you can create visualizations in Explorer — a separate space to explore collected data in detail.

Key characteristics:

Can connect data from other Google accounts: Google Sheets, Analytics, BigQuery, etc.

No official Google support

Limitations on amount of data uploaded:

1000 datasets per user

2GB storage per user

100 uploads per dataset per day

100MB file size limit per dataset

Google Data Studio is free to use.

14. Microsoft Power BI

Microsoft Power BI is a reporting tool that allows you to collect and visualize data, build personalized reports, and securely share them with your colleagues. Microsoft Power BI offers more than 120 free connectors and cloud data sources such as Salesforce, Azure SQL Database, Excel, and Dynamics 365.

Key characteristics:

Free desktop and mobile apps for Android, iOS, and Windows Mobile to collaborate on visualizations

Similar features as other Microsoft products such as Excel — for example, self-service Power Query experience

Can embed analytics and interactive reports into your applications

Pricing starts at $9.99 per month per user if you use a shared processing environment and $4,995 per month for a dedicated cloud.

15. Tableau

Tableau is a visual analytics platform that collects and analyzes your data using machine learning. With Tableau, you can create visualizations using drag-and-drop functionality and employ AI-based statistical modeling.

Key characteristics:

Partially based on VizQL, its core query language, which translates dashboard and visualization components into queries and reduces the need for manual optimizations

Offers a mobile app for iOS and Android

Allows you to integrate your own security protocols

Pricing starts at $70 per user per month.

16. Looker

Looker is a cloud-based data analytics and BI platform that collects and merges data from various sources in an automatically generated LookML model. Looker allows you to set up alerts, dynamic dashboards, and visualizations. A built-in code editor lets you modify automatically generated models if required.

Key characteristics:

Can embed insights from Looker’s BI with Salesforce, Sharepoint, Confluence, PowerPoint, and other tools

To use Looker, you must learn how the basic LookML model works

Looker Blocks feature offers prebuilt code pieces that you can use to accelerate analytics

Looker pricing is completely custom and depends on your specific case, number of users, and the scale of the deployment.

17. Sisense

Sisense is a cloud-native AI data analytics platform that allows you to process and visualize business data. It offers many drag-and-drop tools and interactive dashboards to collaborate with your teammates.

Key characteristics:

Offers custom In-Chip technology to use fast CPU caching instead of RAM, which is slower

Lets you create analytical apps based on your data to embed them externally

Offers separate packages for cloud data teams, BI & analytics teams, and product teams

Sisense has custom pricing, so you must contact a representative to get a quote.

18. Qlik Sense

Qlik Sense is a data analytics platform based on artificial intelligence and an associative analytics engine that allows you to create reports and interactive dashboards. Qlik supports various environments, including the cloud (e. g. Azure and AWS), streaming platforms (e. g. Apache Kafka and Confluent), data warehouses (e. g. Exadata and Teradata), and others.

Key characteristics:

Offers open APIs for REST and. NET

Allows you to embed analytics into your web applications

Lets you create map visualizations and perform geospatial analytics

Pricing for Qlik Sense data analytics starts at $30 per month, though it’s billed annually.

19. Adverity

Adverity is an AI-based data analytics and reporting tool that allows you to automatically collect and merge your marketing data using a data integration module. You can create reports, dashboards, and visualizations using a marketing reporting module and use AI to find patterns and trends in your data.

Key characteristics:

Can connect to affiliate networks, web tracking tools, offline files, TV audience metering systems, and other data sources

Smart naming conventions allow you to avoid errors in reports by highlighting differences in campaign names and suggesting you manually update them

Uses an augmented analytics module to analyze data, applying data mining, statistical modeling, machine learning, and complex algorithms to model user behavior and make predictions

Adverity doesn’t offer fixed pricing. The price depends on how many sources you need to integrate, how many accounts you’d like to have, and which manipulations you’d like to perform on the collected data.

20. SAS Business Intelligence

SAS Business Intelligence is a data analytics and BI platform that allows you to collect data and create interactive reports and dashboards with key metrics you select. SAS BI automatically analyzes your data based on machine learning and automatically highlights the most important parts in visual reports to help you find useful insights.

Key characteristics:

Allows you to combine collected data with geographical data and perform visual location analysis

Uses predictive analytics and algorithms to analyze and visualize data, reducing the need for manual optimization

Can set up bots to reveal insights more easily or connect bots to external services

To get pricing for your company, contact a SAS BI representative.

Conclusions

Data analysis is an obligatory first step on the way to improving your marketing strategy. There’s a huge variety of tools on the market that promise to do it all for you, and we’ve presented the most widely used ones to help you narrow down your search. What’s next?

To find something that will perfectly fit your needs, define your expectations from data analysis, your desired level of detail, and the types of data you’ll analyze. Combine tools that collect, analyze, and visualize data to achieve the best results in terms of quality, convenience, and cost.