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Science of Nurture. Session 4 Module 7. Session Four: Capturing Response and Scoring. 7. Scoring. What you will learn in this module. Key benefits Validates why we score interactions and how IBM and the client will benefit

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science of nurture

Science of Nurture

Session 4

Module 7

what you will learn in this module
What you will learn in this module
  • Key benefits
    • Validates why we score interactions and how IBM and the client will benefit
    • Outlines how scoring facilitates interactions within a client driven and multi-channel Buyer Journey
  • Key learnings
    • We must ensure that we most effectively respond to the needs of the client by implementing a rules-based, testable methodology that prioritizes clients based on readiness to speak to an LDR
    • Scoring is a method of assigning a points value to information captured or implied from the response capture
    • MAT monitors a client’s activity with IBM and assigns a score value after each interaction, and the scoring threshold determines the quality and quantity of leads that are routed to an LDR
    • Scoring determines whether the next step will be Nurture, or route to an LDR
science of nurture education scoring
Science of Nurture educationScoring

7

Purpose

Why

Outcomes

To predictably and efficiently identify readiness to purchase, based on client behavior

To select the best path for client Nurture and optimize use of LDR resources

  • Enables the IBMer to become more efficient and effective by only passing responses that are ready to the LDR and increasing the number of clients in quality conversations with IBM

Who

How we’ll use the brand quality differentiators

2. Making the case with expertise and proven outcomes:

The application of a scoring system will allow IBM to make the case with the most appropriate resource at the right time in order to drive the best outcome for our clients

  • WW
  • DPP select scoring threshold based on analytics
  • DbM performs analytics
  • Agency helps to set up test to improve scoring business rules
  • LOCAL
  • DPP may increase threshold when a response is handed to the LDR, to be in line with local market performance and analytics
  • Setting the shared agenda:
  • Not applicable to this module

3. Collaborating with experts to define future value:

Not applicable to this module

4. Charting the client’s path to deliver that value:

Not applicable to this module

scoring drives the right next step for every client from next offer to conversation with an ldr
Scoring drives the right next step for every client – from next offer to conversation with an LDR

FROM

TO

A single client score intended to assist LDR in prioritizing their work queues

New scoring methodology applied to each interaction within nurture and indicates the client’s readiness to purchase and initiates passing to an LDR

scoring has benefits both to ibm and to our clients
Scoring has benefits both to IBM and to our clients
  • IBM Benefits
    • Smarter routing of responses through system
    • More efficient use of LDR resources
    • More informed discussions with clients
    • Reduce LDR “did not call” rate
    • Increase response: lead conversation rate
    • Increased Sales Accept Rates
  • Client Benefits
    • Content presented is most relevant
    • Interactions take place based on demonstrated need
    • Conversations with IBM LDR and Sales occur when a client is ready
slide8
We need to understand scoring and how it is applied to all interactions, in order to effectively use it for Nurture
  • Scoring is a method of assigning a points value to each response or interaction that is captured (even initial response capture)
  • The higher the score, the further along the client is in the Buyer Journey
  • Inputs used in scoring are collected from explicit or implied interactions
    • Explicit interactions: information captured from response capture (both those that are filled out and those that are populated based upon “cookies”)
    • Implied interactions: information implied by content codes, clicks, and other non-form interactions captured in our systems
ibm analysis has validated that higher scores correlate to better response to lead conversion rates
IBM analysis has validated that higher scores correlate to better response to lead conversion rates
  • The current scoring approach is valid – and ensures better conversion success when LDR follow up with the highest scored responses
    • Higher scores are indicative of higher success – but this is essentially a self-fulfilling conclusion, as higher scored responses are more likely to be followed up with by LDR

High-Level Findings

  • Contacts with total scores greater than 100 have the highest conversion rates, 2x greater than the 41-100 score group.

Among highest scores (140+), conversion rates are very high compared to other scores. This could be because of response type “Call” and/or “Request a Quote”, which have high conversion rates.

slide10
Scores are evaluated after specific interactions to determine whether the client should speak with an LDR
  • The diagram below assumes that the content interacted with has a numerical scoring value assigned to it (example: Whitepaper downloaded during the Compare stage equals a value of X)
  • Scores are cumulative, each interaction updates a clients score

Response Received

Response Rested

Interaction 1

Score Established

Interaction 2

Score Updated

Interaction

3, 4, 5

Score Updated

Scoring threshold achievedSend to LDR

Scoring threshold achievedSend to LDR

Scoring threshold achievedSend to LDR

Immediate send to LDR Sales: “Please Contact Me”

advanced scoring will better identify readiness helping us drive nurture efficiency
Advanced scoring will better identify readiness, helping us drive Nurture efficiency
  • Interaction scoring will be executed within the MAT dynamic scoring engine
  • MAT monitors a client’s interactions with IBM and assigns a score value after every interaction
    • Scores are cumulative
    • Scores expire after a period of inactivity
  • Scoring threshold governs when a client is handed off to an LDR or kept within the Nurture stage
  • A client routed to an LDR will have a baseline level of readiness regulated by a score threshold established within the MAT dynamic scoring engine

How it works

Benefit

slide12
Looking at two examples of scoring outcomes, we can see how the score threshold determines the next step
  • Doug responds to the first touch, but does not download the white paper offered in the second touch
  • Doug’s score is updated after each interaction he makes, but is still not high enough to meet the score threshold and be sent to an LDR
  • Doug does not get a phone call at this time
  • Nurture continues
  • Doug receives a phone call inviting him to a local event for IBM
  • Doug declines, but later reviews the white paper he downloaded and decides to look for more information on ibm.com
  • Doug downloads another white paper and requests a quote
  • Doug’s score is updated, now meets the score threshold and is sent to an LDR

Example 1

Example 2

slide13
MAT score examplesbelow illustrate how scoring will highlight clients whose actions indicate readiness
  • These are illustrative scores. Final values will differ by stage in Buyer Journey in future state scoring
    • If interaction is categorized as Web Response, MAT allocates additional points based on offer type accepted
    • Analytics will be used to validate and refine score values over time
in module 9 we will discuss how to test and optimize the scoring threshold
In Module 9, we will discuss how to test and optimize the scoring threshold
  • The scoring threshold will ultimately determine the quality and quantity of responses that are routed to an LDR
  • Optimizing the score threshold is critical to understanding where the quality/quantity ideal range is for Nurture activity
  • Scoring threshold will be unique to each country and should be based on in-market testing and learning

Score Threshold Example:

High Quality | Low Quantity

Ideal Score Threshold Optimization Range

The middle

Score

Score Threshold Example:

Low Quality | High Quantity

Response Quantity

our scoring is advancing and will continue to do so
Our Scoring is Advancing, and will continue to do so

This is where we start leveraging advanced analytics to help optimize the system

2013

Develop comprehensive analytic model once the data quality and coverage improves – taking into account all factors, including demographics, firmographics, time series.

2012

Develop data improvements and incorporate new data elements and time-based data to reevaluate and improve the approach.

2012

Integrate relevant Science of Nurture work.

2012

Profile recent responders on interaction with multiple programs (to guide the development of multiple scores – by program).

December 2011

Develop deeper analysis that cuts across all scoring parameters (interaction/offer accepted), adding considerations for brands, geos or other high-level breakouts. This will be used to calibrate and improve the current system for scores and triggers.

summary of learnings
Summary of learnings
  • Scoring is a method of assigning a points value to information captured or implied from the response capture and interactions
  • MAT monitors a client’s activity with IBM and assigns a score value after every interaction, and the scoring threshold determines the quality and quantity of leads that are routed to an LDR
  • Scoring determines whether the next step will be Nurture or route to an LDR