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How Householding Customer Data Unlocks Personalization At Scale

7 minutes read

ABM Customer Data Household

Problem: Generalized messaging across customer groups where no obvious linkages exist is because segmentation is detached from the notion of householding within the audience. The problem with this is that it becomes an impossibility to speak to any segment of your audience with any level of authority as messages become more and more uniform in their content and value proposition.  Thereby drowning out your unique voice in a sea of likeness.

Historical Householding View in Marketing

The response of many organizations is to create different communication programs along each possible line of segmentation.  Burning resources, missing opportunity and lowering the overall efficiency of the organization.

The challenge with this is that it chooses a single path on how to engage with the audience or segment members - choosing either the individual, location, role, title or some other defined dimension limits how to respond based on engagement.

Why this is really important is because you’re continuously learning about your audience through additional facts that are being gathered.  It’s these facts which come through things like engagement, VoC and marketing signal data which add to and fine tune the definition of a segment at any moment in time.

All of these need to be continuously fed back into your processes and decisions so you can adapt to the current sentiments within your audience's personalization needs.

There’s a number of factors which come together to solve for this including householding, segmentation and intent.

To breakthrough linear one size fits all messaging the notion of householding needs to be modernized to include the concepts of traditional householding plus accounts plus products or solutions.

Simply put the definition of householding is the relationship between individuals, organizations, location at a moment in time.  Extending on this digital households are ones that share devices, IP addresses and other digital identifiers.  Additionally custom households are those which are defined by behaviors which are connected to you that’s unique to the offering.

How to solve for personalization at scale with the notion of modern householding as a key component of your strategy.  The core process of managing large household data clusters for the purpose of segmentation at scale leverages several technological components.

  1. Connectivity with source systems to create a continuous flexible data integration pipeline between sources and destinations which is rules based.
  2. Use identity graphs along multiple dimensions to group audiences that correlate to relationships, location, entity or products
  3. Have a time based approach to identifying segments that leverages machine learning or a similar capability - the algorithms are critical
  4. Surface the segments through a set of data services that are time based or temporal for syndication or consumption
  5. The results sets or even individuals are then made available via the flexible integrations in step 1 into the consuming systems.
Elsa Petterson

Elsa Petterson
Partner success manager @ Put It Forward

Householding Whitepaper

Whitepaper that walks through the detail of customer householding to achieve personalization at scale.  Includes reference use cases.

Case Study

Failed and stalled project turned around with Put It Forward Integration Designer which reduced overall costs, brought the project in to completion and exceeded the original mandate.

What is Data Wrangling?

Modern tools and solutions are needed to deal with data preparation use cases.  There is more and more data across the organization.  Which is an impossible for IT to manage.

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