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CDP - The Automated Algorithm

Next-generation data solutions are required to stay ahead in the marketplace.

CDP team

Introduction


Modern customer
engagement requires
a different approach to
succeed.

The customer experience has shifted significantly over the past decade due
to disruptive shifts in buying patterns, technology innovation and a dynamic
global marketplace that is ever more interconnected. Today’s customers have
in many cases what seem to be infinite choices among highly personalized
experiences throughout their customer journey. This happens at every touch
point and across multiple channels. Those who create, sell and distribute
products have had to significantly evolve their business models to stay
competitive and increasingly invest in tools and processes to stay in touch and
relevant with customers.

Massive amounts of customer data is being generated and collected
across multiple sources from websites, digital channels and campaigns
to mobile applications. Also the very product itself that consumers are
using is generating data. Retailers who sell, manufacturers who build and
organizations that market products and services have more potential insights
than ever. The problem is not in accessing the data, it’s in creating an
operational model based on data to make effective decisions at scale.

Responding to a customer insight at scale is very difficult to do when the
view is fragmented across multiple channels, products, touch points and
regions. In some scenarios it’s possible to develop a true customer insight or
understanding but it comes long after it’s relevant - often at the point of trying
to understand why a customer was lost.

Furthermore developing a personalized customer experience at scale is
very difficult when other factors such as old data, disconnected systems and
processes and integration complexities are factored into the mix.

These operational disconnects can lead to an unhappy customer,
disconnected experience and deliver a below market expectation resulting in
higher churn, support costs and returns.
In the following sections an examination of how people can start to
operationalize their data when it’s disconnected and move towards delivering
a hyper-personalized customer experience.


The Way Forward - Composable Customer Data Platform


The customer at the center
approach:

Often CDP’s or customer data platforms are looked at as a place to centralize
all customer information that is needed as part of the modern customer
experience platform.

One core question to answer in the quest to develop a winning customer
journey is to answer: Does the C in CDP mean Customer or Centralization?

CDP’s are not new, they’ve been around in one form or another for many years
as a CIM (Customer Information Master), MDM (Master Data Management),
CRM (Customer Relationship Management and DMP (Data Management
Platform). All of these can be components of an operational platform and are
likely part of the existing infrastructure in some form or another. This paper
recognizes CDP as an application that centralizes customer data in a single
location. Specifically bringing data together at rest in a repository to perform
some function.

This traditional architectural or design approach while it has been valid and
does hold a place in the enterprise design model for certain use cases.

customer data platform

Core Needs of the Insight Driven Customer Organization


Time to Insight Activity

How can an insight be acted on the instant its identified?

Insight to action needs to match the pace of decision making at the point
where the customer is engaging. Customers are generating dozens to
hundreds of signals as they engage across channels and their lifetime.
In the aggregate these are in the thousands. These signals need to be
understood at all levels in an instant then turned into an actionable event
that has meaning for the customer. The key is not to just capture the
insight once and act on it quickly, it’s to continually feed that back into
the information loop to capture learnings and recalibrate quickly when
needed.


Customer Insight Driven Operations

How to completely utilize all of the customer data value?

Many organizations are challenged with getting the most out of their
customer data. Combined factors that make this difficult is that just as
the data is distributed across the organization so too must one navigate
through the organizational dynamics to collaborate on a specific need
- spanning operations, technology and business teams. As mentioned
above the traditional approach is to have an internal creator consumer
model of data analysis. Organizations looking to become insight driven
need to move beyond this approach into a more cohesive process.


Siloed Customer Data

Is the most up to data customer information accessible?

Customer data can be found in multiple systems across the organization
- sometimes replicated or aged or mixed with other data. Often representing
a part of the customer experience at a very specific time in their
journey. Consolidating the customer data into a single location has been
a tried approach in many organizations and often is at the root of true
customer insights because the data is incomplete, old or not actionable.

The Traditional Approach - The Data Assembly Line


The data assembly line is often
not a straightforward process
with smooth flowing information
between the point of capture to
insight. It’s often slow, disjoint-
ed and non-reactionary charac-
terized by:

Characteristics of it are:

• One way flows of data and
processes
• Siloed operations and
teams capturing data
• Analytics used for reporting
after the fact - it’s slow
• Disconnected insights from
operational actions
• Insights limited to small
groups of team members

data process flow

Put It Forward’s approach - At the Time of Most Effect


An insight organized under-
standing of the customer that
can be acted on across their
journey. From the various touch
points through their entire
lifetime, across all teams and
understood out into the future.

• Siloed data is crossed with
bi-directional data flows
between systems
• Events are captured from
systems of record and
operational teams
• Process flows are connected
to improve operational
performance
• Insight driven events are
triggered within the process
flows and feedback loops
further strengthen the
insights
• Automated AI algorithms
continuously drive new
insights and better
customer experiences

data process method
Put It Forward analytics

Put It Forward for Customer and Revenue Operations


The Put It Forward intelligent automation platform is designed for organizations
looking to unlock the potential of their customer data and operations. It
connects systems, automates processes and delivers insights through a single
easy to use interface that doesn’t require coding. This helps all teams get on
the same page - marketing, operations, finance and IT - with what is going on in
their customer base.

Disconnected teams, orphaned processes and siloed data limit the capability of
any organization to reach its full potential. Put It Forward was built to connect
these systems and processes together while enabling users of all levels to work
together through a single user interface. This connected infrastructure allows
all teams and players to learn quickly together from the insights while making
operations more efficient.

There is no digital twin of your customer or data required to be built, Put It
Forward from the start works with your data where it is and as it’s being created.
This helps reduce costs of infrastructure, increase the speed of action and
introduce efficiencies into every process through connected insights.

For organizations looking to improve customer and revenue operations with
a CDP the Put It Forward solution gives them the ability to consider another
approach. This delivers customer centric strategies including next best
scenarios, hyper-personalization and lifetime value (LTV) engagement options.

Following are some of the use cases on how Put It Forward can help those
looking to make better decisions with customer data.

Customer and Revenue Operations

Personalized Customer Experience and Engagement

Delphi AI

Next Best Customer:

Using the configurable AI algorithms in Put It Forward you can quickly
identify your next best customer. By integrating all of the customer
behavior together and modeling it against existing and past customers
you can quickly sift through all of the engagement to identify who is likely
to be your next best customer.

Automated Propensity and Conversion Modeling:

Within Put It Forward there are a number of options to understand your
customers through advanced analytics. These models use your existing
data to directly feed into their propensity analysis to quickly identify in
the moment probabilities of customers likely behavior. These identified
behaviors can be used to trigger process flows, data driven events like
an email campaign or a phone call notification through your CRM system
because it’s integrated directly into the Put It Forward Process Manager.

Cohort and Segmentation Analysis:

The ML and AI algorithms go deep into your customers current and past
activity to deliver a deep understanding of what is actually happening.
Then turning that into actionable insights which can be delivered at scale
across your organization from localized operational teams to leadership.


Unified Customer View

Foresight analytics

Identity Resolution:

A central promise of every CDP is that it creates a relationship between
every identifier that is attached to your customer when it’s contained
within a single system. This introduces a bottleneck into the process
flow because it requires all data to be moved. With the Put It Forward
identity resolution function the need to centrally locate your data isn’t
required because the relationships are managed within the system itself
thus leaving your data localized where it has the greatest impact. This
increases speed to value by being able to quickly build associations
between customer identifiers and maintaining the relationship without
having to transport the data to a centralized location.

Single Account and Contact View:

By deduping the overlapping identifiers in multiple systems the Put It
Forward CDP solution creates a single view of the account and contact
for a number of scenarios such as account based marketing, voice of the
customer and the life cycle management. This powerful capability helps
keep everyone on the same page when trying to understand what is
happening with a customer.

Opt-in and Permissions Based Engagement:

Customers face a massive set of options when choosing how they want to
be engaged. An organization’s response to give a customer a single point
of opt out or in can lead to many unintended consequences such as not
being able to communicate with an active customer over a warranty issue
to over engaging when a customer is in a support cycle. Put It Forward’s
identity resolution scenario helps keep all permissions based engagement
synchronized so that you can track current status, trigger process updates
through the Process Designer and integrate new systems that come on
board through the Integration Designer.


Lifetime Value (LTV)

ABM attribution

Customer Value Profiling:

Customers face a massive set of options when choosing how they want to
be engaged. An organization’s response to give a customer a single point
of opt out or in can lead to many unintended consequences such as not
being able to communicate with an active customer over a warranty issue
to over engaging when a customer is in a support cycle. Put It Forward’s
identity resolution scenario helps keep all permissions based engagement
synchronized so that you can track current status, trigger process updates
through the Process Designer and integrate new systems that come on
board through the Integration Designer.

Revenue and Profitability Forecasting:

Knowing which customer to focus on is important and equally so is being
able to create transparency with the finance and operations teams in
an organization. The revenue and profitability forecasting within Put It
Forward allow teams to see across all customer engagements to predict
revenue and profitability of each customer and in the aggregate.

Churn Risk Identification:

The most expensive customer isn’t one that over utilizes your resources
or takes up time with support - it’s the one that doesn’t use anything
and abandons your offer after the sale has been made. Using the same
AI algorithms to identify your next best customer, the Put It Forward
customer data platform enables you to identify which customers have
the highest churn risk or propensity to not purchase another product or
service.


Generative Content:

generative AI content

Generative content creation has the potential to unlock significant
potential within an organization by leveraging its assets and content
history. Here are some of the ways that it is used with Put It Forward.

Subject Line Recommendations:

Where to focus your time and attention in the customer acquisition
process is a critical decision. The AI predictions through Put It Forward
help an organization understand what the potential value is of a customer
as they’re in the consideration phase of their purchase. Knowing where
you should focus your efforts and how to prioritize resources is absolutely
critical to an optimized process. Recommendations on which engagement
process to utilize based on the customers value profile enable the team to
focus and get the most of their resources.

When to Say What:

Similar to subject line recommendations the Put It Forward system helps
identify when to say or send the message to the customer. This is coupled
with the process automation capabilities within the Process Designer to
create a closed loop automation process that frees up people having to
craft manual emails during a fixed window of time.

Personalized Content:

One of the most valuable parts of the customer experience is when
they feel they’re being heard by you. Heard by receiving content or
information that is very specific to their needs at a moment in time. What
Put It Forward does is ingest all of your content into its generative content
engine and based on prompts responds with highly tuned and customized
information for that customer.

Advantages for the IT Organization

Your IT partner is going to have to address many issues when considering
an approach to a CDP within their organization. Including and not limited
to:

  • Speed of insight and data throughput capabilities
  • Set up and maintenance overhead
  • Data quality and governance
  • Infrastructure costs and total cost of ownership
  • Architectural fit

One thing is for certain in the decision process - it’s that there is more than
one way to think about CDP’s and then benefits vary significantly.

Key Takeaways:

• With discernment, determine what the C means to you and your
enterprise teams in CDP and how defining the C helps to deliver the
business outcomes for go-to-market teams.
• Think total cost of ownership (TCO)- what the enterprise is after
insights to drive business outcomes. If CDP’s are not delivering the
insights an additional platform will be required to synthesize, analyze
and surface insights thus increasing TCO.
• Consider integration and technology rationalization. With the growing
number of disparate systems, can the CDP integrate the multiple
disparate systems and help rationalize your technology estate?
• Get alignment on all business initiatives today and potentially around
the corner to ask providers how their systems will deal with the
multiple data sources, data quality, AI models to generate insight and
how the insights will be shared.

Siteline data analytics