Más contenido relacionado La actualidad más candente (20) Similar a Cheat Sheet: Salesforce Einstein for Customer Service (20) Cheat Sheet: Salesforce Einstein for Customer Service1. Cheat Sheet: Salesforce Einstein
for Customer Service
Resolving Customer Inquiries with Automation and Agent Assistance
by Ivan Harris
Founder at Kraytix | Official Member at Forbes Technology Council | C-level product, Salesforce and AI leader |
Author of “Salesforce Einstein Bots Development: Using AI-Powered Chatbots to Enhance Customer Experience” (due end of 2020)
Salesforce®
is a trademark of Salesforce.com, inc. All screenshots are copyright © Salesforce.com, inc.
1April 2020 Copyright © 2020 Ivan Harris
2. Introduction
● Customer service departments are coming under increasing pressure due to customer growth, new service
channels, additional products/languages/territories to support and unexpected emergencies.
● This slide deck summarises Salesforce Einstein features that can be added to Salesforce Service Cloud.
Repetitive inquiries can be resolved using automation, allowing service agents to focus on more complex
issues. For inquiries that cannot be resolved automatically, Einstein-powered recommendations assist agents
in resolving an inquiry more quickly.
● Please do not make purchasing decisions based on this presentation, content is for guidance only, no warranty
is implied or given as to the accuracy of the information. Please contact Salesforce or your preferred Salesforce
Consultancy for further, up to date information, including pricing.
● Views are my own and I hope that you find it useful.
2April 2020 Copyright © 2020 Ivan Harris
4. ● Einstein Prediction Builder
● Einstein Vision
● Einstein Language
● Einstein Reply Recommendations
● Einstein Service Analytics
● Einstein Next Best Action
● Einstein Case Routing
● Einstein Bots (Conversational)
● Einstein Article Recommendation
● Einstein Case Classification
● Einstein Bots (Transactional)
Disruption to business operations can arrive
unexpectedly from many sources, including
natural disasters, terrorism, extreme weather
and health pandemics.
Having a robust plan to ensure business
continuity and recovery back to normal
operations is needed for the survival of your
business.
Throughout these circumstances, customer
service departments come under increased
pressure as customers seek assurance that they
can have continued access to the products or
services that you provide.
If this happens to you, can your customer service
department transition to remote, distributed
working with no perceptible impact on customer
satisfaction and service agent experience?
Is your team able to absorb the spike in customer
inquiries, where many will be repetitive inquiries
related to the emergency that you are managing?
Can you rapidly onboard additional personnel to
assist during the emergency, especially when
some will not be experienced service agents who
come from other parts of your business?
Offer customers the choice to self-service and
for those inquiries that need agent attention,
deflect to lower-cost text channels rather than
the more expensive voice channel.
Assist agents with templated answers to
repetitive customer inquiries, allowing existing
service agents to resolve inquiries faster and
inexperienced service agents to deliver value
sooner.
Automate the end-to-end resolution of highly
repetitive inquires, such as order status and
password reset, using process automation with
no agent involvement.
Business Challenge: Business Continuity and Disaster Recovery
4April 2020 Copyright © 2020 Ivan Harris
Problem SolutionChallenges
Short Term Medium Term Longer Term
6. ● Service Cloud (included with the Service Cloud User feature license)
○ Einstein Article Recommendations
● Service Cloud Einstein (add-on SKU)
○ Einstein Next Best Action
○ Einstein Case Classification
○ Einstein Case Routing
○ Einstein Service Analytics
● myEinstein Platform Services (usage based licensing)
○ Einstein Prediction Builder
○ Einstein Bots
○ Einstein Vision
○ Einstein Language
● Licensing TBD
○ Einstein Reply Recommendations (Pilot)
6April 2020
Einstein Features for Customer Service
Copyright © 2020 Ivan Harris
7. Help:
Trailhead:
Pricing:
Einstein recommends Knowledge
articles to attach to cases and send
to customers.
Fields on cases are used to predict
the most likely Knowledge articles
to recommend.
Recommendations appear in
Lightning Service Console using the
Knowledge Lightning component.
https://help.salesforce.com/articleView?id=einstein_article_recommendations_introduction.htm
None yet
https://www.salesforce.com/editions-pricing/service-cloud/
Available: In Enterprise,
Performance, and Unlimited
editions.
Pricing: Included with Service
Cloud license fee.
Only for Knowledge articles
written in English.
400+ Knowledge articles and
1000+ closed cases required.
Service Cloud: Einstein Article Recommendations
7April 2020 Copyright © 2020 Ivan Harris
Help service agents respond faster by recommending Knowledge articles that will help them resolve a customer’s inquiry.
Overview Prerequisites
8. Help:
Trailhead:
Pricing:
Make next best action
recommendations based on
customer data, business logic
Einstein Discovery models and
Einstein Prediction Builder models.
Automate fulfilling the
recommendation using Flows.
Recommendations appear in
Lightning Service Console using the
Einstein Next Best Action Lightning
component.
https://help.salesforce.com/articleView?id=einstein_next_best_action.htm
https://trailhead.salesforce.com/en/content/learn/modules/einstein-next-best-action
https://www.salesforce.com/editions-pricing/service-cloud/einstein/
Available: In Essentials,
Professional, Enterprise,
Performance, Unlimited, and
Developer editions.
Pricing: All orgs receive 5,000 Next
Best Action requests per month at
no charge. Purchase the Service
Cloud Einstein SKU at $50 pupm
for unlimited requests per user.
Purchase Einstein Next Best Action
Additional Requests SKU at $50 pm
for an additional 10,000 org-wide
requests.
Service Cloud Einstein: Einstein Next Best Action
8April 2020 Copyright © 2020 Ivan Harris
Build business logic to help guide service agents to make the right recommendation to customers at the right time.
Overview Prerequisites
9. Help:
Trailhead:
Pricing:
Einstein predicts case field values
based on the values set by service
agents in historical closed cases.
Recommends field values for
agents to select or automatically
populates fields based on Einstein
confidence levels.
Recommendations appear in
Lightning Service Console using the
Case Details Lightning component.
https://help.salesforce.com/articleView?id=cc_service_what_is.htm
https://trailhead.salesforce.com/en/content/learn/modules/service_case_class
https://www.salesforce.com/editions-pricing/service-cloud/einstein/
Available: In Enterprise,
Performance, and Unlimited
editions.
Pricing: Included in the Service
Cloud Einstein SKU at $50 pupm.
1,000+, preferably 10,000+
historical cases closed in the past
6-months. 100+ cases with the
field-value combination to predict.
Less than 100 values per field.
Supports checkbox and picklist
fields.
Service Cloud Einstein: Einstein Case Classification
9April 2020 Copyright © 2020 Ivan Harris
Save agents time and improve case data quality by recommending field values. Auto populate fields with high Einstein prediction confidence. Then automatically
route cases using auto-assignment rule.
Overview Prerequisites
16. Help:
Trailhead:
Pricing:
Einstein recommends replies to
customer inquiries on the Chat
channel. Agents can post the reply
as is or edit it.
Historical closed chat transcripts
are analysed to create suggested
replies, which can be edited and
approved.
Suggestions appear in the Einstein
Suggestions Card in the Lightning
Service Console.
None yet
None yet
TBC when GA
Available: In Enterprise,
Performance, Unlimited, and
Developer editions.
Pricing: TBC when GA.
Available in English with limited
support for other languages.
10,000+ closed English chat
transcripts required.
Licensing TBC: Einstein Reply Recommendations (Pilot)
16April 2020 Copyright © 2020 Ivan Harris
Improve chat inquiry response times and increase the number of concurrent chat conversations that a service agent can conduct by recommending responses to
chat channel inquiries.
Overview Prerequisites
17. Thank You!
Ivan Harris
Email: ivan.harris@kraytix.com
Website: https://www.kraytix.com
LinkedIn: http://uk.linkedin.com/in/ivanharris
Twitter: https://twitter.com/IvanDavidHarris
Trailblazer: https://trailblazer.me/id/ivanharris
Forbes: https://bit.ly/2x8lLbk
17April 2020 Copyright © 2020 Ivan Harris