Call us Today +1 (888) 240-8088

Dreamforce 2016 is officially behind us, and Salesforce didn’t miss a beat with the roll out of Einstein. The entire event was based around the launch of the integrated Artificial Intelligence program, which is fully integrated within Salesforce. The foundation of Salesforce is finding ways to connect and engage with the customer.


Technology is more sophisticated, and information is more abundant. Every interaction online leaves a data trail to be analyzed. Data is growing exponentially.  How do you avoid getting swallowed in all the data?


Predictive, descriptive, and diagnostic analytics…brought to you by Einstein.

Ask the right questions, use trial and error to find insights automatically. Leverage customer information to provide proactive recommendations. Servicing the customer has evolved to influencing the customer.


AI and predictive analytics are the future.

predictive analytics
predictive analytics


Salesforce knows this. Acquisitions of AI startups MetaMind,, and MinHash, and BeyondCore signaled the rollout of Einstein. Marketo isn’t missing the boat either, launching an ABM solution to complement their core marketing automation business. Wringing more value from data, to benefit the customer. This is the key.


Let’s not forget about the data though. Remember, Salesforce is really just a big empty shell. Data is the filler. CRM’s are useful because they allow users to store and organize customer information. Predictive insights from AI are only as good as the original data.

sources of dirty data


Here lies the core issue: the quality of your data. Einstein sounds great, the presentation was certainly impressive, and it has potential. But predictive analytics mean nothing if the data is cr*p. Technology is knowledge of information embedded in machines. Bad information = poor returns from technology. As it turns out, poor quality data is still the main issue for all Salesforce users.

It always will be.

Dirty data plagues CRM and marketing automation systems, it’s unavoidable. Unfortunately, data ages like fish not wine: it decays. People change companies, job titles, get married and divorced. Data is corrupted on manual entry (forms fills, downloads..), list uploads, and through system integrations.

For all these reasons, businesses cannot neglect data quality as a primary priority. If you want to make use of Einstein’s bells and whistles, start with the basics: take care of your data!


The future of CRM’s and marketing automation systems is in predictive analytics. I’m not disputing the potential of gaining insights from technology. In order to maximize the potential of artificial intelligence you must pay attention to data quality first. Don’t put the cart before the horse. Love your data and you’ll love predictive insights.


The author:

capture,ringlead,sales rebuttals,data quality checklist,rebuttal sales,sales rebuttals list,bad data,ringleads,sales statistics,b2b diagram,crm customer satisfaction,sales stats,call voicemail,data quality analysis tools,data standardization,why is data management important,salesforce hacks,salesforce connections 2015,how to merge accounts in salesforce,salesforce merge accounts,rebuttals for sales,merge accounts salesforce,deduping,not always right,rebuttals in sales,importance of data management,salesforce phone number format,how to standardize data,salesforce implementation,sales motivation video,quality data management,salesforce sucks,motivational sales videos,standardize data,sales motivational videos,list of sales rebuttals,lost lead,sales rebuttal examples,data standardization process,data quality audit tool,best motivational sales videos,what is standardized data,standardizing data,contact capture,importance of data,salesforce customers,why data management is important,improving data quality,data accessibility,crm best practices,merge accounts in salesforce,salesforce administrator resume,salesforce data management,spooky lines,donato diorio,web to lead,data quality improvement strategy,sales team motivation video,dedupe tool,sales motivation,marketo address,sales rebuttals examples,sales motivational speech to sales staff,customers are not always right,data enhancement definition,data quality manager,data quality manager,salesforce certification,marketing automation expert,how to improve data quality,crm and customer satisfaction,database normalization,company swag ideas,salesforce chatter use cases,best motivational videos for sales meetings,sphere of influence definition,sales image,jewel restaurant,sales inspirational videos,salesforce implementation process,reasons why the customer is not always right,importance of quality audit,importance of data quality,data management companies,the customer is not always right,data quality audit,dms launch,why the customer is not always right,salesforce largest customers,staffing procedure,benefits of using a database management system,best sales rebuttals,what is a hot lead in sales,sales motivation youtube,standardize the data,salesforce web to lead spam,types of database management systems,types of database management system,standardising data,improve data,data quality checklist,quality data management,data quality analysis tools,duplicates in marketo,improve data quality,marketo duplicates,merge marketo duplicates,marketo duplicate leads,marketo duplication,data quality manager,data quality improvement,salesforce dedupe,deduplication in marketo,data mining techniques in crm,marketo deduplication,managing data quality,merge marketo contacts,merge marketo accounts,data preparation for salesforce,salesforce phone number format,data quality audit tool,data management for salesforce,salesforce deduplication,merge marketo leads,salesforce data cleaning,salesforce data cleansing,salesforce data management,data quality management tools,data enhancement,data quality platform,data management companies,salesforce merge,data wrangling for salesforce,capture,data enhancement software,salesforce lead capture,salesforce duplicates,lead capture tools,salesforce merge leads,data quality assessment tools,data cleansing,capture tool,best data quality tools,lead prospecting software,data quality management software,data quality plan,data quality management,how to capture leads,prospecting and sales tool,salesforce duplicate contacts,data quality tool,prospecting tool,data cleansing software,database normalization,marketo cost,data operations,salesforce data quality,prospecting tools for sales,data quality objectives,data quality salesforce,lead tool,list building tools,salesforce migration,data quality for salesforce,lead prospecting,list building,lead prospecting sales,website capture tool,prospecting lead,data quality management platform,salesforce chrome plugin,contact google sales,google sales contact,salesforce wrangling,prospecting leads,preparation for salesforce,sales prospecting tools,data cleansing platform,salesforce tool,tool capture,salesforce data migration,sales lead prospecting,prospect tool,prospecting on linkedin,linkedin prospecting,capture emails,data quality software,linkedin salesforce,list builder,data management,data quality,data solutions,web crawling tool,prospecting for sales,how to prospect for sales leads,prospecting tools,salesforce chrome,web crawling tools,smart prospecting,linkedin tools,salesforce linkedin,linkedin for salesforce,research tool google docs,sales prospecting software,sales prospecting,prospecting in sales,sales prospecting sheet,data management platform,data management software,data enhancement platform,database management,sales prospect,marketing automation pricing,data operations software,salesforce chrome extension,prospecting sales,sales lead sheets,prospect research,data base management,sales force tool,marketo price,marketing automation,sales force tools,database management systems,salesforce tools,data operations platform,salesforce preparation,data management solutions,salesforce crm tool