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salesforce.com CRM Solutions
Each of these salesforce.com
CRM solutions are grounded in best practices collected from hundreds of thousands of sales professionals supported over three decades. You will increase the velocity of your sales cycle, eliminate sales bottle necks and maximize your sales team’s effectiveness in less than 30 days.
Baker Sales Systems will help you:
- Significantly expand
the capacity of your sales, marketing and
business development teams
- Improve the
efficiency of your sales prospecting funnel
- Dramatically decrease
your sales cycles
- Promote selling
clarity, motivation and sales proficiency
- Expand the geographic
reach of your marketing, sales and customer
services organizations
- Dramatically reduce
the time required to roll out sales improvement
initiatives
In today's globalized marketplace Customer relationship
management (CRM) is deemed as crucial business activity to
compete efficiently and outdone the competition. CRM strategies
heavily depend on how effectively you can use the customer
information in meeting their needs and expectations which in
turn leads to more profit.
Some basic questions include - what are their specific needs,
how satisfied they are with your product or services, is there a
scope of improvement in existing product/service and so on. For
better CRM strategy you need a predictive data mining models
fueled by right data and analysis. Let me give you a basic idea
on how you can use Data mining for your CRM objective.
Basic process of CRM data mining includes:
1. Define business
goal
2. Construct marketing database
3. Analyze data
4.
Visualize a model
5. Explore model
6. Set up model & start
monitoring
Let me explain last three steps in detail.
Visualize a Model:
Building a predictive data model is an
iterative process. You may require 2-3 models in order to
discover the one that best suit your business problem. In
searching a right data model you may need to go back, do some
changes or even change your problem statement.
In building a model you start with customer data for which the
result is already known. For example, you may have to do a test
mailing to discover how many people will reply to your mail. You
then divide this information into two groups. On the first
group, you predict your desired model and apply this on
remaining data. Once you finish the estimation and testing
process you are left with a model that best suits your business
idea.
Explore Model:
Accuracy is the key in evaluating your outcomes.
For example, predictive models acquired through data mining may
be clubbed with the insights of domain experts and can be used
in a large project that can serve to various kinds of people.
The way data mining is used in an application is decided by the
nature of customer interaction. In most cases either customer
contacts you or you contact them.
Set up Model & Start Monitoring:
To analyze customer
interactions you need to consider factors like who originated
the contact, whether it was direct or social media campaign,
brand awareness of your company, etc. Then you select a sample
of users to be contacted by applying the model to your existing
customer database. In case of advertising campaigns you match
the profiles of potential users discovered by your model to the
profile of the users your campaign will reach.
In either case, if the input data involves income, age and
gender demography, but the model demands gender-to-income or
age-to-income ratio then you need to transform your existing
database accordingly.
Source: Richard Kaith
link
Contact us for a free sales and marketing consultation on the effectiveness of your current go-to-market strategies and to discuss how our RevGen
Sales Systems can improve your bottom line.
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