Self-assessment tool

How AI can
increase your revenue

Discover where AI can have the biggest impact on your business

Which of the following best describes your revenue kink?

Awareness

I am not gaining the attention of enough high quality leads

Engagement

Visitors don’t return and don’t engage in my nurture content

Consideration

I can’t tell when a lead has turned into a prospect

Decision

I can’t get opportunities through my sales process

Growth

I can’t get customers to buy my additional offerings

Retention

My customers churn before expected

Loyalty

My customers defect too easily, small changes to pricing or my offering lead to churn

Advocacy

My customers use my product, but aren’t recommending to their colleagues

Awareness

Revenue Diagnostic

KPIs

Impressions

When Awareness is the revenue kink, your company’s top of funnel is eerily quiet. Just like a retail store with low foot traffic, if a company’s digital traffic is low then all other revenue activity will be impacted. Common symptoms include:

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CAC

A high customer acquisition cost often indicates shortcomings in the Awareness stage.

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ICP concentration

If the visitors that show up to your website don’t match one of your ideal customer profiles, you will likely find your marketing team wasting time sifting through noisy analytics or fielding inquiries from irrelevant leads.

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Referral traffic

Minimal referral traffic indicates people aren’t talking about you which could stem from a lack of awareness, leading to missed opportunities.

How AI can help?

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Lead list creation

Given examples of your ideal customer profile, AI can be used to create lookalike audiences.

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Ad copy

Generative AI can help personalize ad copy so that it resonates with target, for example display ads can reference a user’s city or household demographics.

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Reporting

One of the most common uses of AI in the Awareness stage is in processing large amounts of raw marketing data in order to identify customer behavior patterns, this can save marketing teams countless hours.

Engagement

Revenue Diagnostic

KPIs

TOFU Downloads

Email Signups

Anonymous visitors transition from “Awareness” to “Engagement” when they begin interacting with your brand. The interactions at this stage are often passive, where the user will consume content and in exchange provide hints of what they are thinking via non-verbal cues like their open rate and click rate.

The goal of this stage is to establish contact so that you can nurture the lead and ultimately get them to signify that they are ready to be prospected. When this stage is the kink, you will typically see one of two things happen. Either leads aren’t generated at all, or leads get mistreated as prospects.

Common symptoms include:

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Email signup conversions

Visitors won’t provide contact information in exchange for your proprietary content.

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Unsubscribe rate

When leads are prematurely treated as prospects through offers and other Consideration stage interactions, they are more likely to disengage from the conversation.

How AI can help?

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Personalized nurture sequence

Most companies use a one-size-fits-all approach to their nurture campaigns. If a user signs up for a “how-to” guide, for example, each user will see the same 8 step sequence with offers baked in. If your data is being captured in a warehouse, AI can analyze all of the customer interactions with your website, emails, etc., and automatically route the next best piece of content, whether that be a blog post, a case study, an offer, or any other content that fills the need of the particular lead.

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Customized CTAs

A typical nurture sequence will have CTAs inserted to guide the user toward taking a prescribed action. AI can be used to customize the CTA, either by personalizing the message or the content being requested in exchange for additional content.

Consideration

Revenue Diagnostic

KPIs

Offer CTR

Lead Form Submission

The transition from “Interest” to “Consideration” is subtle, and the two stages often get conflated. But there are distinct changes in the customer behavior. An interested “lead” is kicking tires whereas a “prospect” is seriously considering options. Knowing when to get assertive is the difference between an unsubscribe and a sales meeting booking.

The goal of this stage is to move prospects into the Decision stage by getting them to agree to trial your offering or talk about their pain over a sales call where they become opportunities.

Symptoms of kinks in Consideration include:

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Lead form submissions

When a prospect is seriously considering your offer, they will often ask questions. At this stage they are likely not ready to have a sales call, but will reach out over email/chat. If you provide these channels and are not seeing enough interactions you likely have a kink in Consideration.

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Qualification calls

The overall metric that matters at this stage is trial signups or sales call bookings. If you are not getting enough bookings, it likely means you have not satisfied the prospect’s research questions.

How AI can help?

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Targeted offers

Many companies use rules to determine when to start treating leads as prospects (i.e. if a user clicks on a case study then send an offer). AI can be used to ingest all of the activities of the user with your company in order to determine who is actually a prospect and who is still a lead, resulting in higher conversion rates at each stage of the buyer journey.

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Lead qualification

Similarly, when users submit a lead form submission, AI can be used to score the lead based on the entire history of their interactions with you, providing for better segmentation into opportunities for the sales team and leads for the marketing team.

Decision

Revenue Diagnostic

KPIs

Qualification Meeting Booking Rate

Shopping Cart Addition

First Purchase

The “Decision” stage is often the first place CEOs check when they have revenue problems, because its the point of purchase. But as illustrated, if the earlier stages in the lifecycle aren’t flowing then focusing on the Decision stage is not going to have the biggest impact.

To diagnose whether the Decision stage is indeed the kink, look for the following:

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SQLs (B2B)

This is a highly utilized metric in sales teams, but one that is rife with ambiguity as it depends on the quality of the employee that qualifies the opportunity. If you have an accurate account of your SQLs and your close rate is low, then you likely have a kink somewhere in the Decision stage.

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Cart abandonment (B2C)

If you have a large number of users adding items to their cart but not finishing the purchase, the kink is likely in the Decision stage.

How AI can help?

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Sales qualification (B2B)

Qualifying leads is often an art as much as a science. In B2B environments, sales reps talk with prospects and summarize the conversation into a set of fields in a CRM. Misinterpreting the subtleties of the conversation can mean mis-qualifying a prospect as an opportunity which weighs down the entire sales pipeline. Generative AI, when trained on your sales conversations, can provide a more accurate scoring of your opportunities.

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Cart abandonment recovery (B2C)

AI can be used to predict the likelihood of a customer not finishing their purchase in order to generate targeted offers to keep the purchase process in motion.

Growth

Revenue Diagnostic

KPIs

Upsell Rate

Cross-sell Rate

Many middle-market enterprises rely on single product, single transaction business models, and as such the purchase event from the Decision phase is the main point of new customer revenue. More sophisticated businesses chart out a growth strategy that aligns their business model, product/service ecosystem and GTM motions to force magnify their revenue.

For businesses with multiple products and/or product lines, here are two common metrics to look for in order to determine latent revenue opportunities:

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Upsell rate

The revenue that comes from product add-on or upgrades. i.e. a customer buying more usage of a SaaS product or purchasing a cell phone with bigger memory.

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Cross-sell rate

The revenue that comes from adjacent product lines or services. i.e. a customer buying a bolt-on module to a SaaS platform, or buying a wearable device that pairs with their cell phone.

How AI can help?

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Upsell/cross-sell opportunity identification

If your product or service has digital touchpoints, AI can be used to analyze customer usage to identify customers who exhibit similar behavior patterns to those who have purchased upgrades or extensions, giving your marketing and sales teams warm targets to engage with.

Retention

Revenue Diagnostic

KPIs

Renewal Rate

Churn

It costs 5-7 times more to acquire customers than it does to retain them, making Retention a key driver of revenue. Retention strategies vary by a company’s business model. Subscription business models are often valued higher than transaction models in large part because subscription businesses have more visibility into the customer’s behavior during this stage.

Here are two metrics to look for in order to determine the revenue impact at this stage in the lifecycle:

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Churn

The headline metric for this stage is churn, or the number of repeat customer transactions that occur over a set period of time. Every industry has a natural churn rate, and you can measure your revenue opportunity by comparing your churn rate vs industry average.

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CSAT

One of the indicators of whether a customer is going to cancel their service or decide to purchase elsewhere is customer satisfaction. CSAT can be impacted by the quality of the product experience or the handling of customer interactions.

How AI can help?

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CSAT prediction

Current methods for measuring CSAT rely on surveys which are subject to bias due to the inherent sampling (only 10% of people are willing to take surveys on average). AI can be used to measure CSAT across every customer conversation, even when the customer does not provide a survey. This allows the company to take preemptive actions to retain frustrated customers before they churn.

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Agent assist

One of the most prolific uses of AI in the workforce is in augmenting customer support staff with real-time response suggestions. This can be done via email, live chat and phone interactions.

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Voice and chat bots

Another popular use of Generative AI is in automating customer support entirely through the use of voice and chat bots. The quality of these bots have improved dramatically since the launch of ChatGPT, allowing them to cover an increasing number of customer support use cases (booking service appointments, product troubleshooting, etc). These AI solutions work best in conjunction with Agent Assist, where the workforce provides training data to the AI to improve over time until the AI is ready to handle customer conversations on its own.

Loyalty

Revenue Diagnostic

KPIs

Repeat Purchase Rate

Product or Service Adoption Rate

NPS

Loyalty and Retention both aim to extend the relationship with customers, but differ in the dynamics leading up to the customer’s decision of whether to stay or leave. Retention occurs when a customer completes a purchase cycle under a given set of expectations. Loyalty occurs when a customer continues their relationship even as they experience changes to your offering.

There are generally two forces that affect Loyalty: internal and external. Internal forces are changes your business makes to your product offering (i.e. new products, price increases, etc). External forces are changes that happen outside of your control (i.e. competitor offerings, generational changes in behavior, etc.).

Here is an example metric to look for at this stage:

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Product or service engagement rate

One of the most telling indicators of Loyalty is in the customer’s engagement with your offering. High usage of a SaaS product, repeat visits to an ecommerce product recommendation page, and increase frequency of interaction with your success/services team are all examples that likely mean your product/service is becoming a core part of the customer’s business process or mental model. As this happens the switching costs for the customer increases.

How AI can help?

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Personalization through segmentation

Loyal customers have higher a lifetime value, and are therefore worth more to reward with personalized offers and experiences. AI can analyze customer behaviors in order to identify the subset of customers in the Retention stage who would become Loyal with a customized offer.

Advocacy

Revenue Diagnostic

KPIs

Referral Rate

NPS

Social Media Engagement

The final stage of the lifecycle is advocacy. Advocacy is a natural extension of Loyalty: when you demonstrate to a customer that you can be trusted to have their best interest in mind as you change your offering, they will want to further associate with your brand by introducing their trusted network to yours. The outcome is referrals, or “free” acquisition, leading to a virtuous cycle where new leads enter the customer lifecycle organically.

To determine the revenue opportunity at this stage look at the the following metrics:

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NPS

The Net Promoter Score is a widely used metric to identify Advocates. Through survey questions, it aims to bucket users into promoters, passives and detractors. If your surveys show few promoters, you likely have a kink at this stage.

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CAC

One of the byproducts of succeeding at this stage is referrals, in which your customers bring in new leads organically. This can dramatically lower the customer acquisition cost (CAC). If CAC is your primary concern then this stage should be a focus.

How AI can help?

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Predicted NPS

Similar to CSAT, the current methods for measuring CSAT rely on surveys which are subject to bias due to the inherent sampling (only 10% of people are willing to take surveys on average). AI can be used to measure NPS across every customer conversation, even when the customer does not provide a survey. This allows your company to determine who to engage with for organic growth via social media, testimonials, referral programs, etc.