Setting up your martech stack and activating your ICP

Putting data on tap into practice

For example, Segment incorporates Clearbit data into their foundation by enriching all records in Salesforce. A new lead is populated with firmographic and employee information — job title, phone number, location, etc. — which lets reps save time on research. Enriched data also flows into other tools like Zendesk and predictive lead scoring apps.

With Clearbit, getting customer data into business-critical systems isn’t an engineering roadblock anymore. Just turn on the tap.

1. Data foundation

Your data foundation is one central platform or union of platforms that combines and refines data for (and from) all parts of the business, including:

• Your data from your CRM, MAP, and/or CDP
• Third-party firmographic and technographic data enrichment
• Intent data from website activity
• Any other sources that matter to your GTM

By combining first- and third-party data from many sources, your data foundation closes any gaps in different data types and creates a well-rounded picture of your customers, leads, and unengaged potential customers in your broader TAM.

One example is Clearbit’s Data Activation Platform, which acts as the Grand Central Station of a go-to-market engine. The platform takes in information about leads and customers from your databases, as well as engagement data from activity on your website. It automatically enriches records with B2B attributes, and offers a full view of the market so you’re not limited to known leads.

With this enhanced view, you can design audiences to send to your marketing and sales tools from Clearbit.

2. Segmentation and audience-building layer

The second layer of your martech stack gives you the capability to define segments in your TAM and generate marketing audiences.

For example, you can plug in your ICP criteria to pull a list of your ICP customers and prospects, and select which companies and employees will see a marketing campaign.

Let’s say you’re running Facebook awareness ads for your product design tool for B2B SaaS companies, and you want to target high-level leadership, like managers and directors. You have different messaging for product teams and design teams. You also have different messaging for SMBs versus midmarket-sized companies. In addition, you’re only operating in the US, so you want to weed out companies in other countries so you don’t waste advertising budget on them.

Your segmentation criteria might look something like this:

In this example, you can see how easy it is to isolate the ideal companies for your campaign, and then divide them into four smaller segments for more targeted ads.

Another key segmentation layer is intent. In addition to generating awareness, you may be running retargeting campaigns to move buyers down the funnel. Here you will also want to layer in intent to create ads tailored to specific webpages that have been viewed. Your segmentation may look something like this:

Because the tools in this layer sit on top of your data foundation, you’re creating audiences based on fit and intent data in real time — which means those audiences are dynamic. As people get promoted to Manager, they enter your audience; as they leave for another company, they exit your audience. As a company grows from 100 employees to 120, they move from one segment to another.

Once you’ve defined your audience segments, they should easily flow into other tools and data layer platforms, such as back into your CDP, or out into your email marketing tool and Facebook advertising.

This can be done in Clearbit’s Data Activation Platform via Clearbit Audiences.

3. Activation layer

The activation layer consists of all the many marketing and sales tools you use that touch the customer. These apps put your data to work.

After you define audiences in your segmentation layer, you send them to tools in your activation layer. For example:

• Email marketing platform
• Website personalization platform like Mutiny, Optimizely, VWO, etc.
• On-site chat platform like Intercom or Drift
• Facebook and Instagram advertising
• Google advertising

Today, SaaS companies are trending toward using more and more highly specialized apps in their marketing stack, and this is often most apparent in the activation layer — for example, rather than using one platform as a CRM, email tool, and ad tool, companies use many different apps to achieve one specific goal or create one touchpoint.

Having so many activation apps could get unwieldy, but when they are layered over a data foundation (Layer 1) and a segmentation layer (Layer 2), they can act in a united way — reaching the same ICP prospects with coordinated, consistent messaging across touchpoints.

“Using tools that are best in class, you can improve your data quality 5% - 10%, which means the data you’re serving up in your ads, emails, and to your sales teams is that much better. We are constantly evaluating tools and techniques to improve our own internal data so our processes are smoother, conversations are more personalized, and our ads get to the right people.”

Julie Beynon, Head of Analytics at Clearbit

Step 1: Build the data foundation

Enrich your source of truth (CRM software, CDP software, etc.) with accurate and fresh data. To accurately define your ICP, you’ll want to make sure you have complete firmographic and technographic data (like company size, technologies used, industry, etc.) for accounts in your database.

Step 2: Define success criteria

First, choose metrics that describe your best customers, taking into account your business’s current goals. For example, if your company is oriented toward growing revenue at all costs, your success metrics might be customers with high ACV, low CPA, and ease of conversion. However, if your business is prioritizing sustainability and customer retention, your metrics might be high LTV, low churn risk, or cross-sell potential.

Step 3: Look at the past and identify your best customers

Pull a shortlist of customers who meet your success criteria, using historical revenue data and qualitative feedback from CS and sales.

Step 4: Analyze for shared traits

Identify shared firmographic and technographic attributes these customers have, such as industry or number of employees.

Step 5: Create a sillouhette of your ICP

List out the attributes that will best predict whether a new prospect will be a good customer — a data sketch. For example: “B2B SaaS companies that use Hubspot, have 50–1,000 employees, and have at least $10 million in funding”.

In the next chapter, we’ll show you how Clearbit makes it easy to send your new ICP definition to your go-to-market tools, channels, and motions.