SOLUTION BRIEF. Search-Driven Knowledge & Salesforce to Power Customer Service

Search-Driven

Knowledge &

Salesforce to Power

New Era, New Approach

Customer service has become omni-channel and business-critical, as customers are increasingly mobile and socially networked, and technologies enable ever more dynamic communication. Innovative companies now view customer service as a potent driver of sales and revenue goals, and are architecting programs that position customer service as an essential component of a broader, conversational, and fully integrated customer engagement strategy.

Whatever specific technologies and solutions a company chooses to support its omni-channel programs – from CRM and

contact center platforms, to online communities, forums, IVR, and field service management applications – success in this new era demands customers and agents alike have swift and actionable access to the knowledge and expertise they need, when and how they need it.

Enabling this type of access

can significantly improve customer service KPIs. A recent study by Gartner found that CIOs could reduce customer support costs by 25% or more when an effective knowledge access solution was deployed. The same study found that companies investing to provide better access to contextual knowledge for customers and agents reduced their Time-to-Answer anywhere from 20-80%.1

And such knowledge access can only be achieved with a unified search-driven knowledge architecture.

1 Gartner, “Knowledge Management Will Transform CRM Customer Service,” 2014

Figure 1: The Empowered Customer Mobile, socially connected, 24/7

Social Media Communities Forums Mobile Apps SMS Texts On Site Phone Kiosk In Store Tablet Desktop ? Websites Virtual Chats Contact Center Field Service  Other Customers Influencers  Marketing Sales Customer Service Agents Field Service Personnel

Such an architecture connects, consolidates, and contextualizes in real-time the diverse streams of knowledge being created across all service channels and enterprise systems. It normalizes this diverse data, analyzes it to understand what it is about and how it is relevant, and automatically correlates it with related content on multiple dimensions.

This architecture can evaluate in real-time all of the knowledge being created and shared, and automatically identify experts for even the most nuanced, specialized issues. And when deployed correctly, such an architecture can make this unified, real-time intelligence available to customers, contact center agents, and field service personnel in an intuitive and actionable way, directly within the applications and across the devices they use.

Because such an architecture synthesizes ever-changing, dynamic enterprise knowledge, it can be deployed rapidly with no programming or deep integrations required. And

as the scope and mix of knowledge sources evolves, it can flexibly accommodate.

And finally, because it synthesizes and correlates content from across all systems and sources, it provides comprehensive analytics regarding how customers and agents are finding and using knowledge assets. It helps managers identify knowledge gaps, underutilized resources and emerging trends, and optimize

accordingly.

Fortunately, companies can integrate this architecture into their current systems quite quickly and cost-effectively, regardless of the specific platforms and vendor technologies they use. For those companies experiencing the challenges described in Figure 2, the

Figure 2: Greatest Challenges in Customer Service

and Support

15% 21%

26%

33%

New channels like social media Tracking dept. and metrics Meeting customer expectations Aligning support with strategy Outdated and clunky systems

Knowledge-Centered Service (KCS) methodologies to drive their omni-channel programs, the architecture and approaches discussed in this brief can help make KCS a reality.

For the purpose of this brief, we will highlight how and why such an architecture can be integrated with Salesforce Service Cloud & Communities, the industry’s most complete customer service and portal solutions from Salesforce.com. First we’ll explore the three realities that make omni-channel customer service so difficult to deliver. Then we’ll compare how organizations can address these realities using Salesforce out-of-the-box, versus using Salesforce powered by a unified, search-driven knowledge architecture.

Omni-Channel Success: Why Is it So Hard?

customer service platforms and technologies available on the market. Indeed there are many critically important factors that drive a company’s decision regarding the systems it deploys; factors beyond the scope of this document.

Unfortunately, delivering efficient and effective customer service often proves elusive regardless of the systems a company adopts. This is because traditional vendor approaches disregard three important realities about omni-channel customer service:

Figure 3: Most Used Resources to Solve Support

Cases Web Content Bug/Enhancement DB System Diagnostics Incident History Documentation Knowledge Base Forums

Customer Configuration Info Customer Log Files

Reality #1: Customer & Case Knowledge Resides in Many Systems

companies rarely maintained all customer information in one system. A CRM might store sales and contact data, while a ticketing application might maintain service records. A messaging system stores email communications, while a work order management system tracks all field engagements. A customer’s posts to an online best practices forum is stored only on the WCM, while detailed call information resides in a separate IVR platform.

And rarely does all of the information that can help resolve a customer’s case reside in a single system either. A customer on a community site can’t find the solution he needs because it is sitting in an internal knowledge base. An agent does not realize the answer she needs sits in an email thread between a colleague and another client. A field agent doesn’t know

one of the company’s product managers recently uploaded a document to SharePoint which addresses her issue. Customers, partners, and employees are constantly creating and sharing information that can help resolve customer cases, across a diverse mix of CRM systems, messaging servers, document management systems, collaboration platforms, enterprise social applications, bug databases, social media channels, and more. Unfortunately, this knowledge is not accessible by customers or agents in any sort of unified, efficient manner.

Reality #2: Expertise ID Requires an All System View

The ability to rapidly identify and recruit an expert to help with an issue is essential to service efficiency. Whether it is a customer trying to connect with another customer who has overcome the same challenge, an agent engaging a colleague to help with a complex case, or a field agent finding an engineer who can help solve an on-site challenge, efficiently and swiftly connecting the expert with the need is crucial.

Companies struggle to deliver accurate expertise finding because they do not fully appreciate that expertise is a dynamic and constantly evolving thing. Just like knowledge itself. And because knowledge is constantly being

created, refined, and stored across a diversity of systems, finding the holders of that knowledge requires an “all system”, real-time analysis of the entire team’s work product, correspondence, and service channel activity. Because most customer service tools rely upon the

“raise your hand” approach when it comes to expert identification,2 _{they are naturally prone to manual error}

and neglect. Human beings struggle when it comes to keeping profile information updated, or appropriately tagging their work.

And even if knowledge workers were actively updating their profiles, enabling truly efficient expertise finding still proves a challenge. This is in part because experts often do not know they are experts, or because they are unable to communicate their highly-specialized knowledge accurately in the manual “raise your hand” system.

2 By this we mean that individuals are expected to announce their specific expertise, usually by listing their subject-matter expertise in their corporate profile, and/or manually tagging their work product in some way.

Real-World Success Story

“With operations in more than 100 countries, we must adapt our support and offerings to suit the needs of different customers. … Now I feel more confident about the solutions I provide because of the access to

prior knowledge. I can be sure that I checked all the available information — building on what was done

before — and did not leave out anything.”

– Arnaud, Application Expert, Global Energy Management Company

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Reality #3: Crowd-Sourced Knowledge & Actionable Analytics Are Critical to Success

Because knowledge is dynamic and constantly evolving, the curation of that knowledge must be dynamic as well. And though technology (specifically text and usage analytics) can and should do it’s part to curate knowledge, users must also be able to help shape, refine, and enrich the company’s knowledge assets in the course of their work.

Customers and agents should be able to promote high-value knowledge to peers – quickly and easily – regardless of where that knowledge resides. Additionally agents must be able to migrate or attach high-value knowledge from any legacy system to their primary customer service application. For example, if an agent using Salesforce Service Cloud finds helpful information in the company’s bug database, he should be able to swiftly attach that content to the Salesforce case, and make it “findable” by other agents using Salesforce. (This also supports a fundamental KCS principle of creating content as a by-product of

solving problems.)

To enable this user-driven curation, a powerful usage analytics engine must constantly analyze how users are finding and utilizing knowledge assets. This analysis must leverage granular data about the searches being run, the information and solutions being viewed, and the expertise being put to work. With this real-time analysis, administrators must be able to easily adjust the system’s underlying algorithms to ensure high-value knowledge and expertise is always identified and leveraged efficiently.

Real-World Success Story

“With [Coveo’s Insight Console in Salesforce,] our partners see a great deal of information in a

very small space, enabling at-a-glance account intelligence.”

– Gerard Snippe, IT Manager, Rembrandt & MBO

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Salesforce Service Cloud

Provides organizations with a browser-based console and integrated mobile application through which agents can centrally create, track, route, and escalate service cases. All case and customer data generated within the console are stored

as objects within the Salesforce.com cloud architecture, with additional add-on capabilities that enable an integrated knowledge base (Knowledge) and enterprise social capabilities (Chatter).

Salesforce Communities

Provides an organization’s customers and partners with an online and mobile self-service resource. Like the Service Cloud, Communities can

integrate additional Salesforce tools (e.g. Knowledge and Chatter), and all of the data generated within a Community are stored as objects within the Salesforce.com cloud architecture.

Each of these applications are truly best-in-class, as evidenced by the fact that over 100,000 companies around the world are Salesforce.com customers. But as powerful as they are, their ability to deliver relevant, real-time knowledge to customers and agents is quite limited.

Salesforce: An Ideal Platform for

Search-Driven Knowledge

Using our “three realities” as a framework, let’s discuss how a company using Salesforce Service Cloud & Communities can deliver knowledge to customers and agents with out-of-the-box capabilities. Then let’s explore

how a search-driven knowledge architecture powered by Coveo for Salesforce can help the company better

address these realities. For our discussion, we will focus on Salesforce.com’s two most popular customer service and self-service applications:

Opportunity #1: True Customer Intelligence & Case Knowledge Resides in Many Systems

Salesforce

Salesforce can store and manage significant information about both the customer and their service cases, and Community members and agents alike can perform basic search and exploration of most of that information.3

But the knowledge residing in every system, repository, and service channel beyond Salesforce is un-findable from within Salesforce. Any engagement a customer has had with the company via these service channels can not be used to generate a more complete, real-time customer profile, and any problem-solving knowledge not stored within Salesforce – including legacy knowledge bases, social channels, and the corporate intranet - can not be found from within Salesforce.

This leads customers to leave the community and search the internet for solutions, or call the company contact center because the site can’t deliver the information they need.

This forces contact center and field agents to leave their Service Cloud console (or Salesforce1 mobile app) and log into other enterprise systems to find the answers they need. The agent’s browser fills with tabs to other repositories and systems, and she must waste time searching each of these systems independently.

These inefficiencies delay the resolution of the customer’s issue, and negatively impacts both overall service quality and the Time-to-Value for agents, due to the additional “multi-system” training it requires.

⊲ Customers unable to access all helpful content from within Community

⊲ Agents without unified access to diverse knowledge assets

⊲ Basic search provided across most Salesforce content, but no sorting or filtering options

Community members are offered self-service guidance and content that is relevant to their precise situation, and are able to perform a unified search across all of the systems and sources where the information they need resides. (All with real-time security to ensure they only have access to customer-facing and Community-generated content.)

Informed by a real-time, omni-channel understanding of the customer, the Community will optimize each member’s search results based upon their unique context, and automatically recommend potential solutions, guidance, and peer-to-peer connections based upon what they are viewing at that precise moment. From directly within the Service Cloud console and Salesforce1 mobile app, agents in the contact center and the field are provided a unified, 360-degree view of each customer, harvested in real-time from across all sales, service, marketing, CRM, messaging, social media, and enterprise systems.

They are provided direct, real-time access to all of the available case-resolving knowledge, from across every source where such intelligence resides. They can perform a single search across all systems, and because this diverse content is constantly undergoing deep text analytics and crowd-sourced curation, only the most relevant content is returned.4

Even without running a search, agents will be recommended helpful content based on the specific Salesforce object they are viewing, or issue they are working on at that precise moment.

Agents can use Salesforce as their single “pane of glass” for all enterprise knowledge.

4 This real-time “on-demand” knowledge identification supports a core KCS principle: To evolve content based on demand and usage. Leveraging a search-driven knowledge architecture, the very moment a customer or agent needs the relevant content, it is delivered from across the diversity of “in-motion” knowledge streams and repositories.

⊲ Case-resolving knowledge harnessed from all systems in real-time

⊲ Unified, secure search across all knowledge sources

⊲ Predictive knowledge delivered to agents and customers based upon task at hand

KPI Optimizations

 First Call Deflection

 First Call Resolution

 Average Call Time

 Escalation Rate

 Unresolved Case Rate

 Time to Resolution

 Net Promotor Score

 Agent Time-to-Value

 Agent Attrition

Salesforce

+ Coveo

⊲Indexing connectors crawl all enterprise content sources and channels where customer and case knowledge resides – including Salesforce itself

⊲Diverse content is normalized and consolidated into a secure, unified index, which resides either in the cloud or on-premise

⊲Text analytics identifies the “who, what, when, where, and why” of each specific document, record, message, and conversation from across all systems

⊲Customers & agents are provided unified, secure search against this enriched index, with intelligent faceting, sorting, and instant document preview to explore the results

⊲User and document-level permissions for each system honored in real-time, so users are only delivered content they have permission to see

⊲Coveo Insight Panels integrated directly into the Service Cloud console automatically suggest content & experts based upon the case or object being viewed

Opportunity #2: Expertise ID Requires an All System View

Salesforce

Salesforce enables agents to find experts based only upon the Salesforce Cases people have worked on, and by experts themselves manually tagging their profile with specific skills. (i.e. “raising the hand”.) Salesforce has no ability to identify experts based upon automated evaluation of an individual’s work product, correspondence, or social media engagement. Relying only upon manual self-identification and case data residing within Salesforce itself, subject-matter experts will go unrecognized, and customer service will suffer.

Salesforce

+ Coveo

Within the Service Cloud console, agents are automatically recommended experts based upon real-time analysis of team member’s actual skills and experience.

On Salesforce Communities, customers are recommended other members who might be able to assist based upon their prior activity within the community; and can even be recommended (and swiftly connected to) expert agents in the contact center, should other community members not be able to resolve the issue.

⊲ Automated expertise ID leveraging all-system, real-time analysis

⊲ Experts recommended based upon precise agent/ member issue

⊲ Easily tunable logic to keep expert ID optimized KPI Optimizations

 First Call Resolution

 Unresolved Case Rate

 Time to Resolution

 Escalation Rate

 Net Promotor Score

⊲ Experts identified by manual ID & prior SFDC case ownership

⊲ No analysis of external knowledge sources

In both use cases, real-time identification of expertise takes place through constant, real-time analysis of the company’s diverse and always-evolving streams of knowledge. This helps companies better find and engage the experts among their ranks, and more actively recognize and reward the value of team members.5

How It Works

⊲Text analytics analyzes the index to identify who authored, contributed to, collaborated upon, and is referenced in each piece of content

⊲A multi-dimensional “map” of experts across every possible topic, geography, and subject-matter is built within the index

⊲Experts are displayed every time an agent or customer performs a search, and via the Insights Panel are recommended based upon the specific case or object being viewed

⊲With a single click users can view an expert’s work product to understand precisely why they were identified an expert

Opportunity #3: Crowd-Sourced Knowledge & Actionable Analytics Are Critical to Success

Salesforce

Agents and Community members have some basic ways to curate enterprise knowledge residing directly within Salesforce. Agents are able to attach helpful Salesforce objects (e.g. a Knowledge article) to other Salesforce objects (e.g. an account) and promote it - via “likes” - to peers. But for any knowledge not stored in Salesforce, this critical user-driven curation is impossible.

When it comes to analytics about how knowledge is being found and used, Salesforce provides managers and administrators with no data. Gaining an understanding of what users are searching for, what results they are finding helpful, and what knowledge assets are being utilized in support of specific cases and initiatives is effectively

impossible. And because this analytic reporting is not available – coupled with the fact that Salesforce’s out-of-the-box relevance engine is a “black box” – any sort of tuning to optimize how knowledge assets are found and recommended is impossible.

Salesforce

+ Coveo

Agents and customers alike are able to promote and recommend highly-relevant knowledge with a single-click, so peers with similar challenges in the future can find the knowledge faster. No matter where the content resides, other agents will have more efficient access to it via their Salesforce consoles.

⊲ No search or knowledge analytics captured

⊲ No data regarding how & where users are finding case-resolving knowledge or experts

⊲ ”Black Box” with no search-relevance tuning or predictive knowledge capabilities

⊲ User-level search & knowledge usage data

⊲ Integrated analytics dashboard & reporting engine

⊲ Swift relevance tuning & Insight Panel configuration KPI Optimizations

 Average Call Time

 Customer Defection

 First Call Resolution

 Net Promotor Score

When high-value content is found residing in an external or legacy system, with a single click agents can create a new Salesforce Knowledge article, insert the content directly into the Case Feed, or even attach it directly to the Case itself. This helps companies fully realize one of the core objectives of the KCS methodology: Creating and capturing knowledge as a by-product of solving problems.

And equally important, managers are provided a user-friendly analytics dashboard, accessible directly through the Salesforce Administrator’s console. Dynamically configurable charts visualize how knowledge assets from all systems and sources are being used across a variety of dimensions, including team, content type, content source, path to use, and query rank. Customizable reports reveal key insights such as where gaps in content reside, how long it takes users to discover assets, which assets should be considered

for direct migration to Salesforce (if a phased content migration is a strategic objective), and how the use of various assets are contributing to KPIs such as call deflection, first call resolution, and case escalation. Managers can then act upon these analytical insights directly from their Salesforce Administrator’s console. Using an integrated graphical page editor and a powerful, extensible query language, administrators can precision tune the relevance of the unified search architecture itself, refine the logic driving how and why experts are identified, and adjust the rationale that drives the predictive capabilities of the Insight Panels discussed previously. All from within Salesforce.

How It Works

⊲Customer and agents can promote high-value content discovered from across all enterprise systems, so others find it more efficiently via Salesforce in the future

⊲Single-click migration of high-value content from legacy systems into Salesforce cases, feeds, and Knowledge base.

⊲“Google Analytics” style dashboard integrated within Salesforce generates fully configurable aggregate reports about usage of knowledge assets across teams, geographies, and other dimensions

⊲Integrated graphical UI to configure Insight Panels, and tune the predictive engine that suggests the content and experts the Panels display.

⊲Powerful yet easy-to-understand query language, so administrators can precision-tune relevance for all content across all systems

Coveo for Salesforce

Unified Search-Driven Knowledge for Service

Cloud & Communities Users

For those organizations looking to optimize their Salesforce Service Cloud & Communities deployments in support of integrated omni-channel customer service, consider Coveo for Salesforce.

About Coveo

Coveo makes companies and websites more relevant and responsive, by providing technology that delivers in real time the most relevant, context-aware information for every employee, every customer and every web-site visitor.

Coveo’s transformational technology has been rec-ognized as the most complete, end-to-end search & relevance platform available today. Coveo takes search to a new, more relevant level by securely connecting with and harnessing an organization’s big, fragmented data from any combination of cloud, social, and on-premise systems. The Coveo Advanced Relevance Engine injects the most relevant knowledge into the context of every user, focusing on three business areas to:

⊲Radically boost knowledge management initiatives by making an organization’s collective knowledge easily accessible & relevant, so that all employees can take the best actions;

⊲Inject more relevant knowledge into customer service and sales interactions; and

⊲Personalize online customer experiences within high-end websites and communities.

Coveo is a strategic partner of several leading software companies such as Salesforce.com and Sitecore, and has been recognized as a visionary by Gartner in its Magic Quadrant for Enterprise Search. Among Coveo customers are leading organizations such as Lockheed Martin, Rally Software, and SunGard. For more information, visit www.coveo.com, follow us on the Coveo blog, LinkedIn, Twitter and YouTube.

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