The News
Last week Salesforce announced Einstein Search, an enhancement of the search
mechanisms that are already available in its applications. As usual you can
read the announcement online or below.
Salesforce wants to
release three main issues with Einstein Search:
· The diverse interests and objective of users of
enterprise search make it hard to be as good as a consumer search as delivered
by Google or Bing, or the other consumer search engines, especially if in an
ecommerce environment. In an enterprise setting, objectives can vary between
closing a deal or solving a case, or creating new campaigns. This creates
hidden complexities. There are no safe assumptions.
· Data is residing in different silos and frequently
not linked. Further, there is no one size fits it all as Salesforce as an
application normally is customized to suit an individual customer’s needs
· Third, the data simply does not belong to
Salesforce, with the consequence that Salesforce cannot look into the data,
even not with the objective of improving search. This makes it impossible to
use traditional machine learning approaches.
As per now Einstein
Search is in a private beta stadium with only a few customers using it. General
availability is planned for 2020 but limited to customers on Unlimited,
Enterprise, or Performance Edition plans with 150 or more active licenses for
the Sales or Service Cloud.
So far the
implementation of Einstein Search covers the top 5 searched objects: accounts,
opportunities, contacts, cases and leads, but is intended to support further objects.
According to Will
Breetz, VP of product management for Einstein Search at Salesforce, Einstein
Search is a superset of Salesforce’s available search mechanism. Being implemented
using Salesforce’s AI Einstein it delivers personalized result sets based upon
the first three of the objects listed above. I also covers search in natural
language for all five objects that are in scope although filtering can happen
only around ownership, status, location plus a ‘handful of other filters’. According
to Will Breetz time is not yet one of them. The search ability shall be
improved by GA.
If the confidence
about the result is high enough Einstein Search already provides detailed
information about the result. This is driven by the underlying prediction
model. This model works on the query terms, query independent terms like update
recency and personalization signals that are derived from user behaviour.
With the addition of
customizable ‘next best actions’ Salesforce claims a reduction of 50 per cent
of clicks and page loads, which increases user efficiency and the user
experience.
If you want to
continue reading the announcement here, read on, if you prefer to go on with my
take on it, just scroll down.
If you’re one of the 4.5
billion people
connected to the internet today, you use a search engine to find, purchase, or
learn about pretty much anything that comes to mind. Consumer search engines
provide a seamless way for us to make sense of our complex world. And consumers
are used to a search experience that is fast, accurate, and constantly
improving. But when those same people try to search within their CRM at work,
the experience is painfully underwhelming: too many clicks to find what you’re
looking for and an interface that confuses more than it helps. This shouldn’t
be the case today. Search should be intelligent and help you quickly find
critical information, be more productive, and resolve customer issues faster.
That’s why I am so excited to announce the arrival of Einstein Search,
which brings the incredible power of intelligent search to CRM by making it
personal, natural, and actionable.
The
complexities of enterprise search
Enterprise search has
lagged behind consumer search for a few key reasons. The first is a diverse
user base with a diverse set of goals. When a consumer uses a search bar on an
ecommerce site, the intention is universal: they are looking for something to
buy. But in an enterprise setting, users have divergent goals that can range
from salespeople trying to close deals to service agents solving customer cases
and email marketers creating new campaigns.
The second challenge is
siloed and dissimilar data. For instance, when customers buy CRM platforms like
Salesforce to customize it, they are creating an environment that is completely
unique to their business, from the fields they use to the custom objects they
create. This means that a search model that might work for one customer will
not work for another. At Salesforce, our customers’ data belongs to them, not
us. That's one of our core tenets and why so many companies trust us to run
their businesses. This presents challenges for search because we don't look at
customer CRM data, meaning we can't rely on traditional machine learning
techniques.
Announcing
Einstein Search
Einstein Search
addresses these issues. In building this feature, we had an opportunity to
completely rethink search for CRM. It's already one of the most widely used
features in Salesforce with more than a billion searches a month. And
with our analysis showing an up to 50% productivity lift, we had an
opportunity to fundamentally accelerate customer success at scale for our
customers.
Personalized
results for every user
Salespeople and service
agents rely on Salesforce as their single source of truth for customer
information. This is why we made sure that Einstein Search had the ability to
return personalized results for every user. Each search result is tailored to
what matters at your company and how you work as an individual. For example, if
a sales representative covers accounts in the Northeast in the Financial
Services vertical, Einstein Search will learn that and show them more of what
matters to them. Under the hood, Einstein Search leverages innovative data
mining and machine learning techniques to personalize search results, all while
keeping specific user information anonymized.
Relevant
results from natural language queries
When we type the words
“where can I find the nearest coffee shop” into Google, we expect the system to
render a list of the coffee shops closest to our current location. Enterprise
users expect the same seamless search experience when they use their
applications. Einstein Search understands natural language, specifically as it
applies to Salesforce. For example, if a sales rep types in “my open
opportunities in New York,” Einstein Search interprets that query like a human
would. It’s a faster, simpler way to retrieve whole sets of information (like
every opportunity with your top account).
An
actionable search bar for quicker time to value
Sales and service teams
use Salesforce to get work done. Einstein Search increases productivity by not
only displaying the most relevant information for each user, but also serves up
customizable actions within the search results. For example, instead of
searching for a contact, clicking into their record, and then manually
attaching the contact to an opportunity, you can take these same actions just
by using the enhanced Einstein Search bar. Using Einstein Search can result in
an up to 50% reduction in clicks and page loads for the most frequently-used
tasks, such as editing sales records.
Customers
are finding value right away with Einstein Search
Einstein Search is
currently in pilot, and is already providing value for our customers. Brands
including iHeartMedia and MightyHive are using Einstein Search to spend less
time sifting through data and more time building customer relationships.
“MightyHive is a global digital media consultancy with over 300 employees using
Salesforce, and we are excited about the new Einstein Search
capabilities," said Laurent Farci, Director of Global CRM & Enterprise
Solutions. "It tailors results to individual users, and significantly
reduces the number of clicks to provide immediate access to needed information.”
Einstein Search will be
generally available next year. This feature will be available to orgs with an
Unlimited, Enterprise, or Performance Edition with 150+ active licenses for
Sales or Service Cloud.
Interested customers
can get early access to the Beta release this winter. Sign up for the pilot here.
The
bigger Picture
Enterprise Search is
notoriously challenging and so far has been a domain of third party vendors
that specialize in linking data. On top of the difficulties that are explicitly
mentioned in the press release there are also the topics of authentication and
credentials. Not every user is allowed to use or even see the same data. Enterprise
Search also supports data sources as diverse as applications and file systems,
covering structured as well as unstructured data. These data sources stretch
across all business applications and content/document management systems. As
such it is important to have enterprise search and the data sources connected
to a corporate directory service like e.g. Active Directory.
My PoV and Analysis
With this foray into
enterprise search Salesforce broadens the footprint of Einstein. The early
references are testament to Salesforce offering a valuable addition to its
solutions although it is currently limited to Salesforce applications.
Personally, I am not
so sure that the approach of showing results by objects is the right one but
this may be a matter of personal preference. On the other hand, nothing
prevents me from searching for opportunities with ACME to limit the result set
to opportunities. This can be offered via the search box and/or a more
old-style drop down that supports the search, preferably the search box, though.
Utilizing user
behaviour for personalization is the right approach. It is what we are used to
and it is what matters most, even in an enterprise setting, where one could use
organizational information in addition. Organizational data, however, would
help with people changing roles, and kick in before search behaviour changes
because of a role change, be it the result of a promotion or a reorganization
of the sales force, or whatever. Still, Salesforce having its core on the side
of customer facing interactions I understand that this data might live in
another system that Salesforce cannot access.
Given the limitations
of its positioning – which does not cover the complete value chain of a company
– Salesforce with Einstein Search delivers pretty much the best possible
solution. It should deliver better results than the other built-in searches
that I have seen so far.
I like what I have
seen.
Still, I have two
recommendations.
Salesforce should not
only cover additional objects but also their relations, to be able to answer
questions like ‘ Who do I need to talk to with a question on how to best pursue
opportunity xyz at ACME?’ that needs knowledge about contact persons at ACME,
own employees with their relationships to these contact persons and also
external knowledge. To my understanding the framework to cover at least the
company internal data is there with Einstein.
The second suggestion
is to look into how the technology that was acquired with Mulesoft can help.
Enterprise search is about crossing data silos to combine data to get new and
additional insight. Mulesoft can help here.
I am really looking
forward to hearing more about Einstein Search.
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