how to transform your customer service with intelligent search and salesforce

Search-Driven Knowledge & Salesforce to Power Customer Service

SOLUTION BRIEF

Coveo for Salesforce

Coveo Solution Brief - 2

New Era, New ApproachCustomer 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

architecture this brief describes will help in overcoming

every one of them. And for those companies using

Figure 2: Greatest Challenges in Customer Service and Support

4%

15%

21%

26%

33%

New channels like social media

Tracking dept. and metrics

Meeting customer expectations

Aligning support with strategy

Outdated and clunky systems

Source: Salesforce



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?Our objective is not to compare or evaluate the many

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

Source: TSIA Support Services Benchmark



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

Even before omni-channel service became a reality,

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

Download the Case Study

http://coveosc.coveo.com/~/media/Files/CaseStudies/Case%20Study_Global%20Energy%20Mgmt%20Company.ashx



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

Download the Case Study

http://coveosc.coveo.com/~/media/Files/CaseStudies/Rembrandt_Casestudy.ashx



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.

3 Out-of-the-box, Salesforce provides only a basic, open-source search tool. Besides only being able to index select Salesforce content (it does not enable search of Chatter content, for example), it also provides limited user functionality, including no search facets, and no “type ahead” or auto-cor-rect capabilities. And though Salesforce.com’s Knowledge One search tool does provide limited federation/integration capabilities to a select number of external content sources, such an approach makes unified search, text analytics, and automated “all system” expertise finding impossible.

⊲ 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

How It Works



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


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

⊲ Automated expertise finding for niche subjects impossible



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

⊲ Managers can easily tune the scope and underlying logic that drives the expertise engine

5 A core principle of KCS methodology is to reward - at an individual level - professional learning, collaboration, sharing and improving. The real-time identification of experts discussed in this brief realizes this KCS principle, by recognizing expertise and high-performance far more effectively than any “raise your hand” expertise ID system could.



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


Net Promotor Score

CSAT



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 UsersFor those organizations looking to optimize their Salesforce Service Cloud & Communities deployments in support of

integrated omni-channel customer service, consider Coveo for Salesforce.

To learn more, please visit www.coveo.com/salesforce

http://www.coveo.com/salesforce



About CoveoCoveo 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.

Contact Us

www.coveo.com

[email protected]

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San Mateo, CA

+1.800.635.5476

Canada

Quebec City, QC, Canada

+1.418.263.1111

Europe (EMEA)

Schiphol-Rijk, The Netherlands

+31 (0)20 658 6334

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