Great customer experience (CX) is important for the success of any business. However, understanding the customer experience is hard and being able to quantitatively measure is even harder. Some of the reasons for this are
- Multiple channels - customers may interact across multiple channels of engagement
- Multiple systems - the sales information may be in Salesforce, service information might be in Zendesk or ServiceNow and financial information in Oracle Financials or SAP.
- Data Quality - Same account may have multiple records in the system for various reasons
- Data Staleness - The data that is being viewed by the agent at the time of interacting with the customer may not be the latest information.
- Data Volume - Unlike some business metrics that are only tracked for a few years, customer 360 needs to operate based on data that may be years and even decades old.
SQL Frames provides solutions to most of these problems to create a top class realtime Customer 360 dashboard to understand the customer.
Let's look at how to solve some of the above mentioned problems.
There are two ways to deal with this. One is to extract data from each system into a centralized warehouse and build the customer 360 dashboard from this central system. The problem with this approach is that ETL is a tedious and expensive process not to mention the data is as up to date as the last ETL job.
The other option is to put together the dashboard by pulling the data from each system in realtime. This can be done either by making use of a REST API provided by the system or creating a custom REST API to meet the business needs.
SQL Frames can be used to pull data from multiple systems within the browser to put together the customer 360 dashboard. And because customer data is pulled directly from the underlying systems, the data is expected to be fresh and not stale.
Dashboards and reports are as good as the data you put in them. Hence, unless data qualities are addressed, the resulting dashboards may not be useful. Worst yet, they may give incorrect information leading to wrong business decisions.
Simple to complex data wrangling techniques can be used to fix the data quality issues. While eventually there should be processes in place to avoid such data quality issues entering into the system, these are never ending and what is needed is a nimble way to deal with on going data quality issues as and when they are discovered.
SQL Frames can be used to wrangle with data right within the browser after pulling data using the REST APIs from various systems and then the data can be joined, grouped and pivoted. This intermediate step of data wrangling happens right within the user browser and the wrangling rules can be continuously augmented in the client scripts making it possible to rapidly updates these rules as needed.
Traditional BI solutions work based on expensive ETL operations. Some modern architectures support ELT but still they all operate on the premise of synchronizing data to a central server. Also, due to large volumes of data, most BI solutions limit the amount of data. For example, last 5 yrs worth of data. This type of time limiting the data to deal with performance issues is suitable for internal BI applications but not for customer 360. You may have a customer for the last 10+ yrs and you don't want to make the decision of how to serve them based on the last 5 yrs.
Since a customer 360 operates within the context of a single customer, as long as the underlying systems are able to efficiently provide REST API to get all data related to a customer (which is well indexed), there is no time limit on the data to put together the dashboard.
SQL Frames provides the ability to join, group and pivot data arbitrarily and hence, just pulling all the data related to the customers, potentially across multiple systems, it is possible to stitch together the entire story of the customer right within the agent's browser.
As shown above, it is possible to create a great realtime customer 360 dashboard without expensive backend architectures by leveraging the power of SQL Frames. Reach out to info @ sqlframes.com to learn more.