Similar to most processes within an organization, case management and service operations have seen an increase in expectations, requirement complexity, and overall need for readily available tracking mechanisms. It comes as no surprise that Salesforce has taken swift action on these needs and delivered a one-stop shop for service decision-making in the form of the Service Intelligence application.
In this article, we’ll dive into the ‘why’ and ‘how’ of Service Intelligence, what is included, and how this innovative offering can help your organization take customer service to the next level.
Challenges of Siloed Data
It should come as no surprise that in this day and age, the one deflector preventing companies from achieving the full potential of their customer information to create tailored experiences is siloed data – either split across multiple platforms, stored locally, or not user-friendly enough to digest.
There are a number of factors contributing to this status quo, such as massive amounts of unstructured data and even the lack of resources to start processing and organizing it. All these ultimately lead to an incomplete view of the customer, which is sure to negatively impact both service and sales processes over time. How can these companies quickly mitigate this risk?
Service Intelligence to the Rescue!
This service-specific Salesforce offering is all about connecting the dots between existing data and the need to identify the best action that should be taken to further optimize processes and metrics or offer a better overall experience for all personas in a contact center.
Service Intelligence is primarily an intelligence app that offers actionable insights, analytics, and AI in the flow of work. As it successfully brings together the capabilities of Service Cloud, Data Cloud, and CRM Analytics, it can become the key to answering the most critical business questions through the use of out-of-the-box functionality. The readily available Key Performance Indicators (KPIs) alongside AI-powered insights will take the unknown out of agent performance, customer satisfaction, and even trends across channels.
1. Readily Available Dashboards
The visualization layer of Service Intelligence is CRM Analytics. While you might have heard that complex data manipulation within this product requires SAQL knowledge, in this service-focused offering, a few insightful dashboards based on already existing data become immediately available after the installation. This means that your stakeholders can monitor the metrics that matter to them and their teams right from the get-go!
Every Service Intelligence license includes a CRMA Plus license, allowing everyone to drill down into the analytics as needed. Depending on your organization’s requirements, the out-of-the-box dashboards can be customized. However, keep in mind that future updates will overwrite your customizations hence the recommended route would be to keep them separate if possible.
Especially catered to Service Cloud customers who conduct service operations across multiple channels, the Omni-Studio dashboard under the Channel Performance tab allows service leaders to drill down into both routing efficiency and agent performance. The filters at the top are present on all dashboards, permitting to switch the focus to a specific queue, timeframe, or even a specific agent.
When it comes to routing efficiency, service leaders can use the available widgets to slice and dice the data based on multiple factors to analyze how the volume fluctuates over time. The key metrics at the top provide a bird’s eye view of the work volume, average handle time and speed to answer across the channels, and even the total cost across the interactions.
While the Omni-Channel Dashboard highlights the high-level metrics and volume, the Agents tab surfaces a similar breakdown but, this time, by individual agents, with a focus on KPIs that the team’s performance can easily be measured by when it comes to the workload they are handling. These still include the processed work volume and average handle time but also include utilization percentages and service level, which can help with planning decisions and staffing changes.
Towards the end of the page, the Agents tab gets even more specific in terms of measurable outcomes as more KPIs are surfaced. By switching between Data Explorer topics, managers can review agent performance in certain areas to identify top performers as well as team members who may need additional support and coaching. Additionally, one of the golden contact center metrics, the CSAT based on survey data, is also available if surveys are enabled and in use, offering a complete view.
Moving onto the next Service Intelligence dashboard, the Cases view zooms in on everything managers and service leadership may need for accurate capacity planning decisions backed up by data in your CRM. By following various trends in volume and channel, the workforce can be shifted accordingly. The high-level metrics once again offer an immediate view of the current state of case workload, the average time to close, and even the FCR(%), which is calculated based on the number of cases closed as a result of the first interaction. Of course, if filters are applied, the data in the dashboard, including these metrics, will reflect the filter accordingly.
Towards the bottom of the dashboard, there are more individual data points available, alongside their evolution over time, as well as detailed information about each case. A relatively new addition to this is the Propensity to Escalate column, made possible through Data Cloud’s Einstein Studio, which is used to generate predictions based on various factors such as case age and response time. As you would expect, the model can be updated in accordance with your company’s business requirements and particular findings, in order to prevent escalation.
Since CRM Analytics is native to Salesforce, actions such as those seen in the screenshot can be directly taken at the point of insight , removing the need to navigate to the record to take these actions.
The Spring ‘24 release brought the Knowledge Engagement Insights dashboard to Service Intelligence, which aims to cover the performance and effectiveness of knowledge articles from the company’s knowledge base. The metrics in this view are calculated based on views, internal or external engagement with the article, as well as whether a given article was used as part of an AI-generated response. How cool is that?
Knowledge managers and leaders can quickly explore how an article performed over time and how an agent’s AHT was impacted as a result of either attaching the article or viewing it while resolving a case. Even if customers opt for self-services, their interaction with the article will still be tracked and captured, resulting in a detailed analysis of topics that present the highest interest.
On the same page, an additional Article Analysis functionality is available for granular analysis of each article, providing extra insights and engagement breakdowns by user type and even license type, made possible with the new Knowledge data model object (DMO) in Data Cloud. This level of detail was not only long-awaited, but it is also immediately accessible following the Service Intelligence installation.
2. Einstein Conversation Mining
Only available as part of the Salesforce Service Intelligence offering, Einstein Conversation Mining (ECM) may just be that one hyper-scalable tool your service organization was waiting for!
Successfully obtaining reportable and actionable insights from unstructured conversation data can prove to be a daunting task. Einstein Conversation Mining automatically handles (as the name suggests) the mining process, which consists of identifying common phrases, as well as the grouping and automatic structuring of data in clusters and topics, which can then be further analyzed or even included in automations.
ECM solution is architected to support the mining of millions of records, so even if your organization has been using Service Cloud for a long time, large amounts of data can seamlessly be processed for your team to understand the reasons customers are reaching out.
The catalyst for the mining process is an ECM report that can be created from the dedicated Setup page. Currently, Email-to-Case, Web-to-Case, Enhanced Conversations, and Chat are the supported channels, and while going through the guided experience, you have the possibility to either include all conversations or filter them based on various parameters.
The results of the mining process can be accessed by clicking through the report. From this page, you can actually navigate through all levels your data has been grouped into – up to even the entire transcript of the conversation. Excerpts of the dialog that have been identified as referring to the same subject the customer reached out about are grouped into Contact Reasons, which are then related to a Topic.
Key metrics are available at the Topic level, and the view can be switched between agent conversations and bot conversations. Based on these insights, the topics with the highest frequency and lowest number of back-and-forth responses can be great candidates for automation.
Once insights are discovered, manual interactions can be automated by training a bot through adding a new intent or updating an existing one. This is how Einstein Conversation Mining can enable your organization to not only manually review the contact reason, but also take immediate action to reduce the service agent workload in just a few clicks.
Salesforce Service Intelligence is built on top of Data Cloud, and each license comes with 10K Data Cloud credits per user per month. ECM can be a great way to start your company’s Data Cloud journey since after the results of the mining exercises are pushed to Data Cloud, the Conversation Mining Dashboard will start being populated.
New metrics, such as the average number of turns and the average cost per interaction, are surfaced for the service leadership to drill down into, and the focus can be changed to reflect any of the conversation mining reports you created. In order to slice your data from different perspectives, it is recommended to create multiple reports beforehand.
Similar to the other Service Intelligence dashboards, your team can see at a glance which topics have the highest volume, and further analyze the underlying reasons as well as conversation excerpts.
3. Actionable Agent Insights
While contact center management will surely spend most of their time reviewing the intricate high-level dashboards, service agents need to focus on their day-to-day work of driving their work items to a favorable resolution. Salesforce Service Intelligence allows for customizations as needed directly in an agent’s flow of work by combining Data Cloud powered insights with CRM Analytics visualizations of the most important metrics. These can positively impact the agent’s behavior and flow of work, ensuring that all information is available to drive the desired business outcome.
The Customer Effort Score, which highlights how much a customer has invested in resolving their case, and the Customer Health Scorecard, embedded on a case record page, are just a couple of examples out of a myriad of possibilities of what you can achieve with additional customizations in-house. Both of these are CRM Analytics dashboards, and since record page real estate is limited, it is up to each Service Intelligence customer what and how information, metrics, or KPIs will be exposed to the agent.
Similarly, Einstein Predictions can also be surfaced for agents to benefit from insights while reviewing and preparing to take action on a case. Once again, the Propensity to Escalate comes in handy alongside useful recommendations that may help quickly mitigate the risk of an escalation. Another available prediction, which directly impacts one of the most common agent KPIs, refers to the time for the case to be resolved, offering the agent a recommended next step to potentially still meet their SLA. As mentioned above, these models can be adapted if needed, as each company may discover other factors specific to them that should be considered.
Service Intelligence also includes a My Performance dashboard specifically tailored for agents to provide visibility into their own metrics over time and track their performance in comparison to their team or pre-set benchmarks if needed. This enables them to be aware in real-time of their handle times, FCR, and workload across multiple channels and priorities, in relation to their KPIs.
Setup Service Intelligence
As an out-of-the-box solution, the Service Intelligence Setup has a whole dedicated page within the Salesforce Setup, where all the steps are clearly highlighted based on the order they should happen. This includes everything from the prerequisites for both Data Cloud and CRMA until the actual Service Intelligence installation.
Summary
All in all, combining the functionalities of Service Cloud, CRM Analytics, and Data Cloud into a dynamic and easy-to-consume end result has never been easier!
While Service Intelligence provides a wide variety of out-of-the-box metrics, there’s nothing preventing you and your team from making this solution your very own over time so that executives, managers, and even frontline service agents can easily view, deep-dive into, and take action based on data.
