Each day brings a new technological advancement, and none more gossiped about and feared as Artificial Intelligence. AI is definitely not going away. While understanding how to incorporate it into a workday can put you on the struggle bus, those that leave it on the back burner risk getting left behind rather than getting out in front.
No business unit benefits more from AI than analytics. Data analysis done 100% manually is labor-intensive and error-prone. Through machine learning and automation, businesses can benefit from a faster, streamlined process that more accurately analyzes data, predicts outcomes, and finds insights from high volumes of data. With the help of AI, humans can spot weak points and make improvements through fast-paced judgment and save time spent doing all the routine data cleaning and jockeying into place.
Here’s a deep dive into some of the apps leading in the innovation of AI in analytics:
Clickvoyant
Clickvoyant Pro by Clickvoyant is an AI-driven data analytics platform that integrates with popular marketing technologies to analyze raw data and provide a statistically significant performance analysis. The AI is unique as its algorithms are developed by two women who were Directors of Analytics from the digital agency world. Their company’s SaaS creates easy-to-understand presentations with NLG and they offer the option of analytics consulting services. It’s easy for anyone to use and was built with the digital marketer in mind.
Some analyses out there are NOT statistically significant resulting in “data-driven” decisions that were as good as a random guess. Clickvoyant Pro’s algorithms are optimized to work most efficiently on eCommerce, Lead Generation, Brand, and Media sites giving valuable digital marketing insights and highlighting conversion optimization opportunities.
Providing solutions for agencies, SMBs, and enterprises, Clickvoyant offers a wide range of services, including conversion rate optimization, sales pitch support, assistance with hiring data analysts, staff training on advanced google analytics, analytics product design, and implementation. Pricing starts at $250/month and diversifies with each business’ needs.
TImi Suite
Consisting of four integrated tools to optimize data analytics, TImi suite is a one-stop-shop for analysts and data engineers. Highly developed to handle data sets and predictive modeling faster than other analytics platforms. TImi Suite has a lot of tools available for use for analysts and data scientists:
- Anatella
Anatella is suitable for handling big data. With Anatella, you’re able to easily extract, transform and load all kinds of data sets into any modeling or Business Intelligence tool. Anatella also has a graphical user interface making it usable without code and, therefore, suitable for business users with no programming knowledge.
- Modeler
Modeler provides full automation when creating new predictive models primarily through automated machine learning (Auto-ML).
- StarDust
StarDust provides 3D segmentation allowing you to have a visual display of customer data rendered in 3D and VR. With the ability to detect inconsistent data, StarDust enables you to automatically segment each element in a new data set, which can be used to build a predictive model on Modeler. The ability to segment big data by dozens of criteria and use a VR headset to observe data makes StarDust a unique tool.
- Kibella
Kibella is an open-source platform that offers a Business Intelligence dashboard solution. Ideal for data insights presentations and reports, it enables efficient communication of Key Performance Indicators (KPIs) in a visually appealing way with the help of graphics and the convenience of integrating dashboards into any web page by copy-pasting.
SAS Enterprise Miner
SAS Enterprise Miner is a product of data behemoth SAS. The platform utilizes data mining tools to analyze data sets through predictive modeling techniques, particularly for SMEs and big businesses. Although the platform has a graphical interface unit, it is primarily made for data miners and statisticians. Its core function is to shorten the time it takes to build models with the ability to guide business users with limited statistical knowledge through the data mining process and generate analytics results in understandable charts to provide valuable insights that aid in the decision-making process.
SAS Enterprise Miner offers in-depth analytics through a suite of statistical, data mining, and machine learning algorithms that facilitate advanced descriptive and predictive modeling. The platform allows for easy comparison of models with the ability to display them side by side while saving them as templates that can be used to tally new data sets without starting over. Mistakes made by manually rewriting and converting code are mitigated as the scoring code is automatically generated through each step of model development.
OpenText Magellan
OpenText Magellan is an AI-driven open-source platform that utilizes advanced analytics and machine learning to enhance business processes. The platform can acquire, merge, manage, and analyze structured and unstructured data stored in an Enterprise Information Management system and external sources. The data can then be presented in an easy-to-understand format through shareable interactive dashboards and reports allowing you to identify patterns and trends. From this data, you can gain valuable insights on company operations.
OpenText Magellan can better analyze and interpret data through machine learning, further enhancing accuracy and predictions made over time. It has a text mining feature capable of analyzing billions of pages of video, imagery, and audio using an algorithm to examine any piece of text and determine its relevance. It is marked especially useful in picking up hate speech and mitigating it from going further by analyzing sentiment, emotion, and intention in texts. OpenText Magellan also uses computer vision technology to expose visual threats such as alcohol, drugs, or violence.
Through its wide range of capabilities, the platform can compile and analyze different data sets and present it in an understandable format while using Machine learning to improve the data analysis with time.
