ABS Playbooks

A data-driven sales system, built upon proven account-based sales frameworks that can establish a predictable revenue engine and scale it effectively.

What is TAM?

TAM stands for Total Addressable Market. Often investors, economists, and journalists refer to TAM as the combined turnover value of a specific industry in a certain region. An example would be, “The B2B SaaS companies TAM in the US is worth $xx Trillions”

For B2B sales teams, the amount of turnover in one vertical or industry is not actionable. 

What is actionable is to know the number of companies or the number of contacts within one company that a sales team can target based on their Ideal Customer Profile(s) (ICPs).

Often, the B2B sales teams that use the term TAM have an account-based selling (ABS) and/or an account-based marketing (ABM) approach, meaning they clearly understand their different ICPs. They have documented them and organized them by verticals and/or key accounts with specific playbooks on how to approach them.

They also have different ideal personas based on the ICP type and their influence on the decision process.

For example, if your ICP is retail, 80% of your TAM will be made of companies with the following business model: omnichannel (sells online and offline), pure player (sells only online), and brand (can sell directly online or omnichannel + via other retailers or only through retailers). But you will also identify 20% of other retailers with the following business model: D2C (omnichannel and pure player), travel, telco, etc. Based on this, the company size alone can differ for each ICP type. Web traffic is a better indication of size for pure players; the number of stores and web traffic can both apply to omnichannel retailers. But for brands, the number of employees will often give you a better indication of the company size.

The size criteria must be used to correlate the potential deal size with prospective customers.

Finally, based on the size and the ICP type B2B sales team will most likely target different personas as they will have different KPIs based on the above-defined business models...

See the examples of documented Retail ICPs and the guidelines to map your own ICP.

What is an account-based sales (ABS) playbook?

A sales playbook is commonly used by sales teams to define documented sales processes that deliver results. 

We like categorizing playbooks based on two categories: revenue type and funnel level.

Revenue type
Outbound comments
New business
Go-to-market (GTM)

The goal of this playbook is to close the gap of your TAM. In other words, add ICP accounts that are not yet in your CRM to your CRM.


The goal of the recycling playbook is to recycle IC accounts that are dormant in your CRM with new contacts or recontact the same contact with a different approach.

Key accounts landing (KAL)

The goal of this playbook is to map the TAM of personas for large accounts across departments, subsidiaries, and regions. This playbook works best with accounts that have at least 5K+ employees. This playbook can be used to bring new revenue key accounts.


Hacks are non-scalable initiatives that can boost the pipeline based on time events/triggers. E.g. Booking a meeting at a specific trade show, conference, or online event, Tracking the persona of existing customers that moved to a new ICP company, job ads alerts, etc.

Customer success
Key account expansion (KAE)

Expand revenue to new departments or regions of existing key accounts.


Renew revenue from past customers.

Go-to-market (GTM)

You usually want to use this playbook when your organization and sales team are still in the early stages in terms of revenue traction. The main goal is to validate the assumptions about ICPs and personas by generating revenues from the targeted TAM. 

Later on, based on traction, the goal will be to reverse engineer the data behind the accounts and contacts in the CRM. This data can be used to adjust the GTM strategy and recycle companies already in CRM with higher chances of conversion based on data. For example, a sales team can choose to re-focus their GTM strategy and only target companies of a certain size in one vertical, as the conversion with these 2 data points is 50% higher. The same approach could be applied to recycling companies in the CRM that did not move down the funnel.

The more unified the company and contact data are, the better the sales team can leverage data-driven sales. This will depend on how specialized the sales team is from day one. If you can’t invest in a specialized sales team for your GTM, the good news is that you can always catch up with CRM data hygiene debt. This can actually be part of your recycling.

If there’s one thing you don’t want your sales reps to do (especially at the early stage) is to enter data in the CRM instead of speaking to prospects. 

Note: the GTM playbook can be used to enter new markets for later-stage companies.


Depending on your positioning and the size of your TAM, a meaningful part of your TAM will already be in your CRM from the GTM efforts. That being said, having a company that matches your ICP in a CRM doesn’t mean that the sales team has found nor connected with the right prospect(s) that can influence or make decisions. 

Even if these prospects have been identified, the average connection rate (across all the channels in B2B is somewhere around 8%). Best B2B sales teams strive to get above 20%, which still means that 80% of the prospect you outreach to will not get back to you.

Finally, in large organizations, 8% to 12% of the executives will change roles (internally or externally) every month. In other words, 8% to 12% of your contacts' data loses accuracy every month. Hence the need to recycle the dormant TAM already in your CRM. You can implement fully automated CRM stages on the account level to identify the different types of dormant accounts. See the guidelines for Salesforce, Hubspot or Pipedrive.

This process requires but is not limited to checking for new events (funding/acquisition announcement, technology change, market condition, etc.) that could trigger new assumptions about PAIN and/or look for new prospects based on predefined personas from the documented ICP.

Below are the benchmark rules of accounts recycling timeframe for dormant accounts based on the number of employees.

KAL (new biz) / KAE (CS)

These playbooks are used to target, land, and expand large accounts with at least 1,000 employees. These organizations often make decentralized decisions for each department/business unit and regional office.

These large organizations also have their unique organizational structure with a specific structure that only applies to them. This means that you need to map and document every single account separately and adjust the ICP documentation for accounts and personas accordingly.

Landing your first deal from such accounts may take months or even years. The good news is that once you have penetrated an account, you start using the Key Account Expansion playbook and expand the account horizontally across departments/regions, and your outreach becomes naturally much warmer.

Often when sales teams have dedicated key account programs a TAM can be made for each account, and in that case, the TAM stands for the number of prospects available for each key account. 

For example, if the key account is IBM, then the sales team will map relevant departments and job title structure and, based on their research, evaluate the TAM of prospects that matches the personas from the ICP documentation.


Hacks are non-scaleable playbooks that can be used to generate tractions based on predictable event-based triggers. While not scalable to deliver predictable growth, the triggers are event based and easy to track. For example, if your team is planning to attend an event, you could scrape the list of attendees and book meetings at the event with them.

Another example for mature B2B companies is the clients Alumni hack. For example, if you have been in the market for some time, many of your clients will change jobs and most likely move to a new role internally or in a new ICP company. Proactively tracking this type of trigger event can help to generate a new warm pipeline.


Proactively re-targeting past clients based on timing events, new feature launches, or because your old contacts left the company can definitely be a source of pipeline, especially if the product/service you sell is not subscription-based.

Funnel levels & playbooks

Playbooks must be applicable at all funnel levels to support your sales team.

Top of the funnel (TOFU)

For this part of the funnel, playbooks will consist of training, guidelines, processes to map, organize and enrich accounts that match your ICPs in order to capture your TAM in your CRM. Additionally, you will need separatel processes to identify and enrich key personas with relevant data points and contact details for ICP accounts.

To manage these playbooks effectively, specific automated ABS stages will need to be implemented on the account levels in the CRM to manage accounts pipelines better and work with your TAM. See guidelines for Salesforce, Hubspot, and Pipedrive. You can also copy our Gsheet playbook templates with API integrations for TOFU enrichment see guidelines here.

The goal of the TOFU playbooks is to generate a predictable number of accounts and contacts that matches your ICP criteria.

Middle of the funnel (MOFU)

Playbooks for MOFU will consist of training, adjusted templates, and guidelines to contact personas on multiple channels (phone, email, LinkedIn, and mail) as per the best practices. The playbook will be adjusted for each persona and ICP to create a scalable outreach system with as much granularity as possible to optimize conversion.

To manage the playbooks effectively, specific ABS pipeline management stages will need to be implemented on the contact level and integrated with sequencing tools to automate pipeline management workflows and activity tracking. See the guidelines to integrate OutplayHQ with Salesforce, Hubspot, and Pipedrive.

The goal of the MOFU playbooks is to generate a predictable number of Sales Qualified meetings as per the persona and ICP criteria.

Bottom of the funnel (BOFU)

BOFU playbooks will consist of training and best practices documentation to discover and align potential fit with personas working for ICP companies.

The goal of the BOFU playbooks is to generate a predictable number of closed opportunities and consistently (over)reach revenue quotas.

See example of a Sales Enablement Academy to onboard, train and upskill your team with TOFU, MOFU and BOFU playbooks.

Funnel levels & tracking

In order to forecast accurately, you must track your playbook pipelines with a full overview of the funnel stages. This dashboard must be reviewed weekly to adjust game plans and have an agile ABS approach.

ABS Playbooks & Tools

If your sales team is specialized, you will also need to set up your CRM to manage different types of pipelines for TOFU, MOFU, and BOFU. Additionally, separate tool stacks will support your team in implementing various playbooks on TOFU, MOFU, and BOFU. See more on the 6D ABS tools’ dimensions.

ABS Playbooks & Data-driven Sales

Your capacity to leverage data-driven sales will highly depend on the specialization of your sales team and tools setup. Your salespeople have no interest nor incentive to enter data not related to their pipeline management into the CRM, and salespeople should never work for the CRM. The CRM should work for them.

However, if you have a Lead Research team that is following TOFU playbook guidelines and using the correct tools, then you will have unified data across all your funnel stages. You can use these data points to adjust TOFU strategies based on how your MOFU and BOFU pipeline data points look like.

Note: If you can’t invest in a lead research team or do not have the resources to implement the right tools, and processes, then you may begin to incur CRM hygiene data debts where the data in your CRM is not unified through your funnel. The good news is that you can always catch up with your CRM hygiene data debts later on. It might be a time-consuming process or an expensive project if you want to do it fast, but it’s something you can always rectify. Alternatively, you can always re-unify the data as part of the processes with the Recycling playbook.


1. What are the main differences between SMBs and Enterprise TAM?

SMBs consists of two types of TAM:

Dynamic: This means that your TAM is growing rapidly every month. Dynamic TAMs are mostly generated by strong demand in a specific sector. For example, the e-commerce sector boom in the late 2000s and the rise of fintech since 2010.

Static: These TAMs are often composed of professional service companies. While you often have new agencies, law practice, consulting, and accounting businesses opening, you have the same number of companies shutting down. These TAM are very large yet competitive and very stable in size. 

Enterprise TAMs are only composed of one type of TAM:

These are very large players that have been established in the business for many years. Often companies are a few decades old and have thousands of employees if not tens of thousands.

We call this TAM mature. They are also very static however are composed of very large companies. Once one account becomes a customer, it can often be expanded horizontally across departments and regions.

2. How do B2B sales teams can capture their TAM?

The most common solution for B2B sales teams to capture their TAM are the following:

  1. Scrape data from publicly available sources
  2. Export data from databases
3. How accurate is TAM data for B2B sales teams?

Data from the database or scrapping is rarely 100% accurate for various reasons.  Once the cleaning process of the initial TAM starts, you can use the ratio of reviewed companies vs. ICP (Ideal Customer Profile) to estimate your adjusted TAM.

If you target SMBs companies you should be able to target 1000s if not 10k+ accounts. If you target large Enterprise companies you should be able to targets a few 1000s or a few 100s very large companies with 1,000 of employees if not more.

For e.g., if your initial dataset from scraped or exported data is 1,000 and 40% of the companies you reviewed match your ICP criteria after reviewing 100 companies, you can estimate that your adjusted TAM is 400 companies from this specific dataset.

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