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Is your sales data ready for Salesforce Einstein?

31 October 2019 Amy Green Sales Intelligence

Einstein can do amazing things, but only if the data it’s analyzing is accurate and reliable.

According to Salesforce:

“Data quality is important to CRM even without AI because quality data helps reps increase efficiency, build trust with customers, and use Salesforce effectively.

When you add AI to the mix, data quality becomes even more important. The predictive models behind Sales Cloud Einstein are based on your Salesforce data, so having complete, accurate data helps Einstein give you the best predictions, recommendations, and insights.”

Why the quality of your sales data may not be sufficient for Salesforce Einstein, and how to fix it

The days of relying on intuition and guesswork to make important business decisions are over.

It should come as no surprise that sales organizations that rely on data and analytics to inform their decision-making outperform the competition in all areas.

According to research by McKinsey Global Institute, data-driven organizations achieve a significantly higher likelihood of above-average performance across the entire customer lifecycle:

  • The likelihood of generating above-average profits is 126% higher for data-driven companies.
  • 50% of data-driven companies are likely to have above-average sales, compared to only 22% of their less data-savvy competitors.

Data-driven companies are 2.6 times more likely to have a significantly higher ROI than their competitors.


Source: McKinsey Global Institute

However, even though most business leaders now realize the importance of being data-driven, McKinsey’s research also found that most sales organizations today (57%) still do not view themselves as effective consumers of advanced analytics.

Salesforce Einstein promises to solve the big problem of “Big Data”

By 2020, the number of digital bits of information stored on the web will reach 44 trillion gigabytes, according to EMC.

This rapid explosion of data has led companies worldwide to begin hiring Data Scientists as fast as they can in order to make sense of it all. 

According to the Harvard Business Review, Data Scientists are “a high-ranking professional with the training and curiosity to make discoveries in the world of big data”.

Unfortunately, the August 2018 LinkedIn Workforce Report found that there was a shortage of more than 151,000 people with data science skills nationwide, with “acute” shortages in New York City, San Francisco, and Los Angeles.

The lack of data science talent is causing serious constraints to organizations, not only in the U.S., but worldwide.

Fortunately, new technologies are being developed to fill these gaps and not just help organizations tame their large stores of data, but turn them into valuable insights that can increase performance, efficiency, and profitability.

One of these new tools is Salesforce’s Einstein AI.

What is Salesforce Einstein?

Salesforce summarized the capabilities Einstein that provides in a blog post introducing the technology:

“Powered by advanced machine learning, deep learning, predictive analytics, natural language processing and smart data discovery, Einstein’s models will be automatically customized for every single customer, and it will learn, self-tune, and get smarter with every interaction and additional piece of data. Most importantly, Einstein’s intelligence will be embedded within the context of business, automatically discovering relevant insights, predicting future behavior, proactively recommending best next actions and even automating tasks.”

One way of thinking about Einstein is that it’s a “Smart CRM Assistant” that works in the background to perform time-consuming tasks, find connections in your data, provide actionable insights, and ensure that each member of your sales team is able to make the right decision, at the right time, based on data.

With Einstein, the benefits of data science and AI are no longer restricted to highly-skilled data experts, or large organizations with enough capital to develop their own Artificial Intelligence programs.

Salesforce aims to “democratize” data science and AI, so that business people of all kinds “can direct the analysis without having to fight for scarce data-science resources. Suddenly hundreds — or even thousands — of business users can run their own analyses, unlocking their own opportunities for improvement.”

What results have other organizations achieved by using Einstein?

According to Salesforce, some examples of specific customer success include:

  • 2.35x increase in lead conversion of top-ranked leads with Sales Cloud Einstein Lead Scoring
  • Increase open rates on new product emails to 71% as compared to 8—15% open rates without Einstein
  • 9.6% increase in conversion rate and a 15.5% increase in revenue with Commerce Cloud Einstein Product Recommendations
  • Accurately flag compliant display images 98% of the time with Einstein Vision to increase field rep productivity

Is your sales data ready for Salesforce Einstein?

While Salesforce’s Einstein AI looks incredibly promising, there is one critical problem that can not only cripple the value you are able to get out of tools like Einstein, but can also cause your entire sales analytics program to fail.

That problem is this:

Einstein can do amazing things, but only if the data it’s analyzing is accurate and reliable.

According to Salesforce:

“Data quality is important to CRM even without AI because quality data helps reps increase efficiency, build trust with customers, and use Salesforce effectively.

When you add AI to the mix, data quality becomes even more important. The predictive models behind Sales Cloud Einstein are based on your Salesforce data, so having complete, accurate data helps Einstein give you the best predictions, recommendations, and insights.”

While Salesforce has listed their full data requirements for Einstein here, there are additional consequences of having unreliable data, beyond not being able to use Einstein:

Common data quality problems

Some of the most common data quality problems organizations deal with are:

  • Missing records: Forgetful or busy salespeople often neglect to enter complete data for every lead, contact. and opportunity in the CRM.
  • Duplicate records: When one sales rep loses contact with a contact, and another sales rep begins interacting with them at a later point, a second record is often entered into the CRM for the same person. If the contact has moved or changed companies, they might show up in so many account records that it’s difficult to even determine who they are anymore.
  • Incomplete records: Customer records are often missing key data, such as email or phone number. Company accounts are often missing key data, such as company size, industry, and revenue.
  • No data standards: Salespeople are often not 100% certain about which pieces of data are required, which are optional, or how to enter data in a consistent manner. For example, if customers in the state of California are entered as living in the state of CA, Calif, Cali, and California, you might find that a regional breakdown shows that you have customers in 87 states.
  • Stale data: Data is constantly changing. Data that was accurate yesterday might be completely inaccurate today. Accurate data means up-to-date data.

So, how will you get your sales reps to accurately and thoroughly collect all of the critical data from their sales activities and customer interactions (such as calls, emails, texts, meetings, etc.), and then manually enter all of this data into your CRM?

Without this data, not only is advanced AI technology like Einstein rendered useless, but your entire sales analytics program is put into jeopardy.

Manual data entry continues to be the #1 biggest obstacle

You can only derive valuable insights from your sales activity and customer interaction data if you’re collecting it in the first place. This is where the biggest challenge lies for most sales organizations. 

The process of manually entering this into a CRM such as Salesforce is often extremely tedious and frustrating, decreasing the chances that your sales reps will actually take the time to do it.

In fact, sales professionals cited manual data entry as their #1 biggest challenge to using their CRM, according to HubSpot’s State of Inbound: Sales Edition Report:


Source: HubSpot’s State of Inbound: Sales Edition Report

The report goes on to state:

“Data entry time negatively correlates to user satisfaction. Practitioners and executives alike prefer time spent selling to time spent on manual tasks that software should help avoid….”

There’s no wonder why only 40% of sales updates are ever entered into the CRM, on average, according to ActiveCampaign. Even when data is entered into the CRM, there’s no telling how accurate it is. Even small typos by hurried salespeople can ultimately add up to major errors down the road.

Unfortunately, even cutting-edge technologies like Salesforce’s Einstein AI aren’t capable of forcing your sales reps to collect and manually enter this data in a thorough and accurate manner.

While getting sales reps to enter accurate and thorough data is an uphill battle, you simply can’t afford to not have this data.

The only viable solution is to find a way to eliminate manual data entry entirely and make the whole process automatic. However, until recently, there has been no reliable technology capable of doing this.

How to automatically collect sales data + improve data quality with ZynBit

Fortunately, Sales Force Automation (SFA) tools have become extremely helpful at automatically handling all kinds of mundane, tedious administrative tasks.

According to SiriusDecisions:

“These improved systems are capturing information automatically so that reps spend less time doing data entry, and they’re analyzing the data they capture to help reps target the best prospects and accounts, offload tasks such as calendaring, and guide reps using insights from the SFA data. SFA systems are finally becoming a valuable tool for reps and sales operations.”

ZynBit, for example, is an SFA tool that works transparently in the background to automatically record and track 100% accurate sales activity data so your team is free to focus on more important activities, like attracting, delighting and retaining your customers.

With ZynBit, your sales reps can carry out their work like they normally do, sending emails, booking appointments, making phone calls, etc. As they work, ZynBit automatically tracks all of their sales activities, without them having to think about it.

By eliminating manual data entry, ZynBit gives your sales team hours of valuable time back that they can use for high-impact sales activities and coaching.

It’s like having a virtual sales assistant working behind the scenes to record events in Salesforce, book meetings, and find the data-driven insights your team needs to deliver sales quotas.

With ZynBit:

  • Your sales reps always know how to prioritize their pipeline
  • Managers know where to focus to improve team performance
  • Sales leaders can easily see the data they need to optimize strategies and goals

ZynBit makes Einstein possible

Salesforce’s Einstein AI technology leverages machine learning to uncover patterns in your data and provide valuable insights that can improve decision-making, increase efficiency, and expand your sales team’s capacity to satisfy more customers and close more deals.

However, Einstein can only provide these valuable insights if the data in your Salesforce account is thorough, accurate, and up-to-date.

ZynBit makes sure that your Salesforce account is always up-to-date with 100% accurate sales data so that you can take full advantage of all the powerful features Einstein has to offer.

Try ZynBit Free for 14 Days

If you’re ready to see how ZynBit can help your sales organization become data-driven, sign up for your free, 14-day trial here.