Turning Data Into Gold

3. Turning data into Gold

Introducing the first-party data framework

Wherever you are in your journey, this framework will inform each step towards a first-party data strategy, your catalyst for B2B growth.

3.1 Acceptance

Gaining consent to use first-party data

Before you can use any of the data you’ve collected, it’s important to have rights to use this information in your business. Depending on the data source, this can take many different forms, from user agreements when signing into a new product, through to cookie consent and preference centres when visiting your site.

The risks of not handling this correctly can be severe for many businesses. In addition to potential financial penalties for data misuse (GDPR Info EU, n.d.), an inadequate consent strategy could lead to missing out on a substantial amount of valuable data (Jon Busby, 2024).

Once you have secured consent, it may be tempting to request excessive information from your users. However, many users now understand the value of their own data and may be reluctant to hand over more permission than they feel is necessary.

Complete the gaps yourself

Only collect what you need using your own first party (and if necessary, third party) data to complete the gaps.

For example, a lead form can be easily supplemented with third-party data from a provider such as ZoomInfo, turning just an email address into a treasure trove of information, without overwhelming your user with a lengthy form.

In our studies, we have found that incorrectly applied consent not only could represent a risk, but could result on up to a 75% reduction in your analytics measurements”

Jon Busby, 2024

First-party Data Framework

Acceptance

Consent to use first-party data

Are you collecting data in way aligned with the privacy expectations of your customers?
Are you compliant with the evolving global legislation?
Are you taking advantage of the latest in Machine Learning to complete gaps in your audience data?

Analytics

Using data to make decisions

Is data accessible by your teams in your organization – or data siloed?
Do you use dashboards and data when making marketing and sales decisions?
Are you teams enabled to tell stories using your data to justify decision making?

Activation

Targeted marketing through data

Are you using all your data sources to create audiences?
Are you segmenting your data effectively to create and target new audiences?
Can you activate your first-party data in the market as part of your media campaigns?

Automation

Decrease time to market and reducing wastage

What systems need to be connected to make your marketing more real time
How can we use automation to speed up the flywheel?
Where are you wasting marketing resources on prospects that aren’t ready to buy?

AI

Create new personalized experiences

What can we be doing today, to make our campaigns more effective tomorrow?
Can you use AI to optimize your campaigns?
What can you do to introduce personalization into your customer journeys?

3.2 Analytics

Using data to make decisions

After identifying your sources of first-party data, the next step is to consolidate it in the right place. These systems are often managed by various teams within the organization. For instance, while your web and media platforms may fall under marketing operations, your customer support system—another valuable source of first-party data—might be handled by the customer success team. The same holds true for your CRM and transactional systems.

Make no mistake, breaking down data silos across multiple teams in an organisation is a substantial digital transformation undertaking, and with any large transformational project, it requires strong leadership support.

Join forces to bring it together

Your first port of call here should be to your manager, highlighting the benefits of bringing this data in from across the company. Establishing a Data Steering Committee can help to give all teams a voice in the solution, but it’s important not to over-engineer the solution as you build it out. This is a marathon not a sprint.
Once it’s in one place you can start to build analytics that help look for patterns in the data.

Uncover exciting truths

To get started, think about building a hypothesis that you can prove out using your new consolidated data. As you get more advanced you can start to add cluster analysis or advanced data techniques to uncover previously undiscovered segments from your data.

3.3 Activation

Targeted marketing through data

Your data is now in one place, so it’s time to take advantage of this to make your marketing more effective. The first step is to defining audiences based on your consolidated data. To start, this step can be as simple as defining a single audience (especially if you are just testing the hypothesis from the last stage), but can expand in complexity and specificity as you become more comfortable working with the data.

Working with your ABM teams to build out audiences can be another great way to get started—as these target audiences should already be well-defined, you should be able to clearly demonstrate an impact with your consolidated data.

Once you have defined audiences, you can act on your data at scale through media partnerships. This means pushing your audience lists to other platforms as targets of your campaign. This can take two main forms:

Customer Matching – This is where your data is matched 1:1 out in world with the individuals (or companies) linked to that data. For example, if “Fred” visited your site, downloaded a whitepaper, and provided consent (of course), and you used this data to re-target, Fred would now see your advertising out in the wild.
Lookalike or “Predictive” Audience Matching – This expands your first-party data to look for similar prospects that are similar in type to your provided data.

It is critical that in either of these scenarios, you should still require consent before targeting a user’s data, and that when you do supply this data to your partners, it will be in a privacy-first compliance method, such as with one-way encrypted email addresses. Leaving personally-identifiable information data exposed could lead you open to a data breach, fines, and reputational damage.

3.4 Automation

Decrease time to market and reducing wastage

If you’ve followed the process so far, you’re in a good position to make the most out of your first-party data — but don’t stop now. You might be ignoring a valuable set of leads if you don’t take the time to explore data flow automation to reduce dataset wasting and to reach out to this untapped audience with purchase intent faster.

This is a part of many platforms, but it can be easily held up with internal data reviews restricting real time access and integration across platforms. By working with a hyperscaler or a data provider of choice, like AWS or Snowflake, to incorporate privacy-first mechanisms, you can alleviate concerns from your legal and compliance teams, creating a scalable privacy-first platform.

3.5 AI

Create new personalized experiences

There will be many advantages to using AI in the customer journey before the data harvesting step, from personalizing content, through to cutting through to what’s important in your data.

We recommend that businesses focus their efforts on reviewing, deploying and evaluating AI. This is no different from traditional digital transformation deployments—and an approach that centres around agility, curiosity, investigation, flexibility with various AI platforms will prepare your organization for the next round of AI innovation.

Marketing AI Maturity Curve

73% of B2B customers say generative AI
will help companies better serve them”

Salesforce, 2024