Data is available in higher volume, from more sources, with greater complexity than ever before. Businesses that implement a consolidated view into the disparate data silos will have greater insights and make better business decisions. In the past, this meant a data warehouse, and physically moving the data into one repository. Now we have Business Intelligence (BI) tools like Signals that can provide a one-screen view to the data. The best feature is ease of use; anyone can use the platform, not just data scientists.
The Importance of a Holistic View
Data driven companies are using insights from data analytics to give them a competitive advantage in the marketplace. Businesses need to have access to a unified view of the various data silos, viewing the data holistically, and not just individual data sources. The view can include employee data as well as customer data, internal data as well as external data. Progressive companies do not limit data access to a central data scientist role in IT or Marketing; any business analyst can leverage the unified view.
Sources of Silo Data
Sources of data silos include surveys, chat, user reviews, emails, CRM, support tickets, Excel spreadsheets, server logs, crowd sentiments, social media, video, and a host of other locations. The data may be accessed through built-in data connectors to websites and online retailers, and by uploading data files. When the business analyst is presented with a one screen view to these data silos, insights can be made and decisions improved.
Use Case: Product Management
Let us look at an example of an analyst wanting to see how customers are reacting to a new product line. The analyst can analyze user reviews on retails sources such as Walmart, Home Depot, and Lowe’s, access social media comments on Facebook and Twitter, video comments on YouTube, and chat sessions and emails with customer service. The way a distribution channel interacts with the customer can have a direct impact on sales results. The data may indicate sales performance and customer satisfaction are higher at Home Depot than those at Lowe’s (or vice versa). Taking a deeper look into the ‘why’ of this data may reveal comments from customers on the product placement and display in the store, the access (or lack thereof) of help, and their overall buying experience. A single view into multiple data silos can often shed light on recurring themes and issues with the product and channel. It can also indicate if the trends are improving or deteriorating. These details would otherwise have been buried in the data silos.
Use Case: Customer Service
In the case of customer service, the employee and customer sides of chat sessions and emails can be viewed on one screen. (See our blog post: Data Analytics on Chat Sessions.) Key themes, insights, and trends may be observed on both the employee and customer side. The key to making this holistic view is analyzing the data as if it came from a single database. Recurring themes in customer service may indicate the need to update the posted FAQs, add features to the product, or improve the buying experience. These insights are gold for the Product Manager responsible for the performance of the product.
Varied Data Types
We see more variable data types today than ever before; sensors, medical devices, GPS data, crowd sentiment, and other data sources often appear in unstructured format. A text analytics tool can bring this data together in an easy way, making it easy for the analyst to manage and draw insights from the data. Multi-language support is crucial for any business, ensuring the voice of the customer is heard regardless of the native language.
Use Case: Competitive Analysis
Product Managers can analyze competitors and the feedback, issues, and concerns raised by their customers. Competitive research is a terrific use case for BI tool sets. Knowing how customers are reacting to your competitors may shed light on opportunities to improve and advance your own product. Bringing the data silos together means more than just viewing sentiment analysis or performing a price comparison. A unified view of the data can strip away the surface data to access core, systemic issues and themes in the data sources.
Use Case: Human Resources
Internal data silos may be analyzed in much the same way. Let us look at the Human Resource (HR) functions involved when an employee is hired, reviewed, and when they depart. HR should have a data repository of the interview notes from when the employee was first hired. Each year companies conduct performance reviews, documenting strengths, weaknesses, areas to improve, and other feedback. When an employee leaves an organization, there are exit interviews. Much of this data will be text, and in unstructured format. A good data analytics tool can bring these different data sources into a unified viewpoint so insights may be made about the process, and action plans generated to improve employee retention and performance.
An Easy Way to Get Started
Taste Analytics Signals platform can easily analyze your different data silos, bringing them together for side-by-side comparison. Signals provides data visualization, providing the key buzzwords and categories and showing trends over time. Our built-in data connectors to Walmart, Amazon, Home Depot, Lowe’s, Yelp, Facebook, Twitter, Apple store, Gmail, Google Play, YouTube, Salesforce, Etsy, etc. make it easy to view external data sources. You can put your internal data into a CSV file and upload it. Drag and drop your CSV file at any time you want on Signals.
Ready to get started? Sign up for a free trial of our platform and try it for yourself.
Questions? Contact us by emailing clientsupport@tasteanalytics.com.
