How well do you know your customers? How often do they buy? What motivates
them to make multiple purchases? How can you ensure long-term loyalty?
How can you attract and retain new customers?
And, most importantly, how can you cost effectively align your marketing
campaign to ensure that you are sending the most relevant message to
each customer segment at the time they are most likely to buy?
The number-one asset of a company is its customers, and a close second
is the information about those customers gained through operational
customer relationship management (CRM) systems.
Leading marketers have taken advantage of the powerful benefits of
sales force automation, call center software, and other CRM systems to
identify customer demographics, track purchases, monitor shopping habits,
and identify product preferences. As a result, they have been able
to maximize the interaction between company and customers, increase
sales, and build a loyal customer base.
Managing this wealth of valuable customer information as a strategic
asset, however, is what makes the difference between simply tracking
customer behavior and capitalizing on that information to understand
and optimize the financial value of each customer.
Predicting customer product preferences and purchasing habits,
and crafting the most relevant marketing messages around this information,
requires a carefully orchestrated mix of intuition and an analytical
framework that supports fact-based decision making.
Without an analytical structure in place, even the savviest marketer
will have difficulty manually analyzing all of the complex information
they may be gathering on customers. And, while still a powerful resource,
an operational CRM system alone will struggle to provide the deeper
customer understanding required to add value to every interaction with
each customer.
Predictive analytics, including data mining, are needed to provide
a clear picture of what is going to happen, in order to take
the most effective action. The predictive analytic process discovers
the meaningful patterns and relationships in data, separating signals
from noise, and provides decision-making information about the future.
For example, which customers will be buying what next, or which customers
are likely to defect? By supporting CRM with predictive analytics,
companies of all sizes can begin to manage customer information as
a strategic asset when developing marketing campaigns. Doing so will
result in better decisions on what message to send, and to whom and
when to send it.
Understand customers
Using typical data-driven segmentation approaches, companies
can easily uncover literally thousands of attributes that define
customer behaviors. However, with so much data it becomes too difficult
and time consuming to manually process the information for efficient
fact-based decision making. Predictive analytics that supports the
operational CRM system automatically scans the data and “crunches” it
quickly so that marketers can go in to query the results and get
specific answers. With the results of the multidimensional customer
profiles applied to current marketing campaigns, the interaction
with the customer is optimized to be more relevant, more appropriate
and targeted for increase response frequency.
Develop targeted offers
Once marketers gain a deeper understanding of their customers, they
can more easily target specific offers to their most profitable customers
and promising prospects. Applying predictive analytics to determine
customer propensities toward certain product categories enables better
decision making in selecting the right products to promote. Moreover,
predictive analytics can help marketers to more accurately analyze
the results of targeted campaigns, revealing patterns in customer
behaviors and preferences that subsequently can be leveraged for
unique product offers.
Execute campaigns in real time
With specific messages and marketing channels in place for specific
customers, a CRM system enhanced with predictive analytics can achieve
real-time customer recommendations. Individual customer predictions,
or a model that assigns scores based on customer behaviors, help
marketers match the most relevant product offers based not only on
the frequency, but also on the complete range of demographic and
purchasing behavior data available for each customer. Because the
scoring process evaluates past data to forecast the probability of
future customer behavior, marketers can tailor their CRM systems
to respond with specific offers for specific customers, a strategy
proven to increase response rates and optimize the value of each
customer.
Match a specific offer to a specific
individual
Predictive analytics facilitates propensity modeling, which enables
marketers to fine-tune specific messages to specific customers within
each marketing channel, e-mail, direct mail, website, call center,
and determine what approach elicits the best response. By employing
propensity modeling using predictive analytics, marketers can quickly
isolate different customer segments and replace a “one-size-fits-all” campaign
with an individualized, highly relevant message tailored to the customer’s
profile that results in a higher response rate.
Monitor campaign results
With predictive analytics in place, the entire CRM process can be monitored
to determine whether the current marketing campaign is generating
the expected results. Customer metrics can be easily tracked and
continually evaluated, providing instant insight into current customer
behavior as well as statistically sound calculations to help marketers
predict future activity. By keeping a close eye on customer metrics
such as sales, retention rate, and churn propensity (the likelihood
that current customers may be lost to competitors), marketers can
revise marketing campaigns to respond to the customer’s actual
behavior at any given time and continue to monitor the success or
failure of marketing efforts.
Satisfying customers in today’s highly competitive global marketplace
has never been more challenging. Having a deeper insight into customer
expectations and future behaviors is the key to successful marketing
campaigns. Predictive analytics enables marketers to understand the
key factors that drive customer value and loyalty, and it attracts
more customers.
To find out how you can leverage analytics in your own marketing campaigns,
please contact
Alan Ogilvie at info@computerworks.bc.ca
or 604-552-4008.
