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How to Shape Long Term Behaviors for Customer Acquisition Objects
How to Shape Long Term Behaviors for Customer Acquisition Objects

Conversion Rates, Setting Sales / Customer Targets, Rank Strategies, Improving Strategies Over Time, Paid Acquisition vs Unpaid Acquisition

Kelvin Hudson avatar
Written by Kelvin Hudson
Updated over a week ago

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Overview


Introduction to Shaping Customer Acquisition:


What does it mean to "shape" customer acquisition?

  • You want the number of customers you bring in to grow over time by changing the initial values of your input metrics and adding assumptions to them. You then want to reference the revenue streams in the annual view to determine if the number of customers you've set the model to forecast translates into a reasonable amount of revenue. If you revenue is too high, you're bringing in too many customers (assuming your price assumptions in revenue are correct) and if revenue is too low you're not bringing in enough customers (assuming your price assumptions in revenue are correct.)


Which "assumption" types should you be using and when?

  • Optimize Metric Value- This is how you set long term targets for the metric you'll be changing (example: "I'd hope to have 30 partnerships established by June of 2025"). You'll apply this assumption to the number of affiliates, partners, or any source you have that puts you in front of more customers.

  • Optimize Change Rate / Growth Assumptions- These change types represent growth that may be static (in the case of a "growth assumption" or maybe even variable growth (optimize change rate) but the key concept here is that you use one of these assumptions when you can't definitively say that the growth will stop. You'll apply this assumption to the number of inbound leads per partnerships, number of inbound leads per partnerships, "top of funnel", and any other metrics that describe actual "traffic". For example, because you can't reasonably expect the number of website visitors to stop growing beyond a certain number, you'd apply one of these assumptions to show it changing over the entire life of the model.


The Goal of "Shaping" Customer Acquisition

  • Good news! In just about every case the goal is always "to bring on more customers". This means that you should expect to increase the value of every metric that will result in more customers over time (top of funnel, leads, # of partnerships , etc) and decrease the value of metrics that will limit the number of customers you acquire (namely just the "cost per click" metric inside of the paid advertising strategy).


Best Practice / General Advice for Conversion Rates

Conversion rates listed can be considered generally acceptable / safe / defensible but the point of using your financial model month to month and monitoring your company's individual performance is that you are using these values below until you have enough historical data to plug in values from your own historical performance.

The most defensible numbers you use will always be the numbers based on real data that you establish over time. For example, below you'll find a conversion rate of 2.5% for Paid Advertising; this is a conservative figure to use at the moment, but if you find that 3-6 months from now (or have 3-6 months worth of data now) that you find your ad performance is closer to 6%, then the number you should use as your conversion rate is 6%, not 2.5%.

  • For the Conversion Rates Provided below 10% allow for a range of +/- 100%

  • For the Conversion Rates Provided above 10% allow for a range of +/- 50%


Organic Website Traffic:

  • Conversion Rate: 0.5%

  • Top of Funnel - Input the number of leads you currently have visiting the website

    • Add either a "Growth" or "Optimize Change Rate" Assumption to the "top of funnel" metric and input values that either feel attainable, if you have no data, or the values you have from your historical data.


Paid Advertising

  • Conversion Rate: 2.5%

  • Budget- Input your starting monthly budget.

    • Add an "Optimize Metric Value" assumption to the Budget and put in a target value for the highest amount you'd reasonably expect to spend month to month in ad spend as well as the date you'd like to reach this value.

  • Cost Per Click- Input your starting cost per click value (the amount it costs you to acquire a qualified lead, not a full customer).

    • Add another "Optimize Metric Value" assumption here and put in a target value for what you feel you can reduce the Cost Per Click to and the date to reach this value by. Typically aim to reduce your starting value by a range of 25-50% of its initial value. Example, if starting with $10 CPC you should aim to decrease it to anywhere from $7.50-$5.00.


Affiliates

  • Conversion Rate: 2%

  • Number of Affiliates- Input the number of affiliate partnerships you're starting with.

    • Add an "Optimize Metric Value" assumption to the "Number of Affiliates" and put in a target value for the highest number of affiliates you'd reasonably expect to establish partnerships with as well as the date you'd like to reach this value.

  • Inbound Leads Per Affiliate- Input how many potential customers an adequately performing affiliate is expected to put your company / brand in front of each month.

    • Add either a "Growth" or "Optimize Change Rate" Assumption to the "Inbound leads per Affiliate" metric and input values that either feel attainable, if you have no data, or the values you have from your historical data.


Conferences

  • Conversion Rate: 5%

  • Inbound Leads Per Conference- Input the expected attendance per conference

    • Add either a "Growth" or "Optimize Change Rate" Assumption to the "Inbound leads per Conference" metric and input values that either feel attainable, if you have no data, or the values you have from your historical data.


Influencers

  • Conversion Rate: 2%

  • Number of Influencers- Input the number of influencers you currently have representing your Brand / Company

    • Add an "Optimize Metric Value" assumption to the "Number of Influencers" and put in a target value for the highest number of affiliates you'd reasonably expect to establish partnerships with as well as the date you'd like to reach this value.

  • Posts Per Influencer Per Month- Input the Number of times the Influencer Shouts out your Brand / Company

    • Add an "Optimize Metric Value" assumption to the "Posts Per Influencer Per Month" and put in a target value for the highest number of posts you'd expect from an influencer within a single month.

  • Inbound Leads Per Post- Input the expected audience size for each post

    • Add either a "Growth" or "Optimize Change Rate" Assumption to the "Inbound leads per Post" metric and input values that either feel attainable, if you have no data, or the values you have from your historical data.


Customer Referrals

  • Conversion Rate: 20%

  • Referral Percentage- Input the % of customers you're expecting to tell a friend about your company / brand.

    • Add an "Optimize Metric Value" assumption to the "Referral Percentage" and put in a target value for the highest % of people you could see referring your company / brand within a month as well as the date you'd like to reach this value. This is usually won't be above 33% because if we convert this into regular speech, it could be hard to justify that more than 1 out of every 3 customers (33%) can be expected to refer customers each month.


Partnerships

  • Conversion Rate: 20%

  • Number of Partnerships- Input the number of partnerships you're starting with.

    • Add an "Optimize Metric Value" assumption to the "Number of Partnerships" and put in a target value for the highest number of partnerships you'd reasonably expect to establish as well as the date you'd like to reach this value.

  • Inbound Leads Per Partnership- Input how many potential customers an adequately performing partnership is expected to put your company / brand in front of each month.

    • Add either a "Growth" or "Optimize Change Rate" Assumption to the "Inbound leads per Partnership" metric and input values that either feel attainable, if you have no data, or the values you have from your historical data.


Email Marketing

  • Conversion Rate: 1%

  • Mailing List Size- Input the number of people you email each month

    • Add an "Optimize Metric Value" assumption to the "Mailing List Size" and put in a target value for the highest number of people you'd reasonably expect to email in a single month as well as the date you'd like to reach this value.

  • Average Emails Sent Per Month- Input the number of times the same person is emailed each month

    • Add an "Optimize Metric Value" assumption to the "Average Emails Sent Per Month" and put in a target value for the highest number of times you'd reasonably expect to email the same individual in a single month as well as the date you'd like to reach this value.

  • New Inbound Leads Response Rate- This is interchangeable with the click through rate / open rate / % of people you expect to open the emails.

    • Add an "Optimize Metric Value" assumption to the "New Inbound Leads Response Rate" and put in a target value for the percentage of people being emailed you expect to interact with the emails as well as the date you'd like to reach this value.


Content Marketing

  • Conversion Rate: 1.5%

  • New Pieces of Content- Input the number of posts per month you currently expect to make.

    • Add an "Optimize Metric Value" assumption to the "New Pieces of Content" and put in a target value for the highest number of posts you'd reasonably expect to publish each month as well as the date you'd like to reach this value.

  • Inbound Leads Per Piece of Content- Input how many potential customers an adequately performing post is expected to put your company / brand in front of each month.

    • Add either a "Growth" or "Optimize Change Rate" Assumption to the "Inbound leads per Partnership" metric and input values that either feel attainable, if you have no data, or the values you have from your historical data.


Evaluating the Number of Customers You're Forecasting

Switching into the Annual View

  • Switch into the Annual View by Using the Dropdown in the Upper-Left Hand Corner

  • Pull the Timeline out to Reflect 6 Years

  • View each year's value of "Total New Customers" Independent from one another- this is not a running total year over year, instead, it's the number of customers expected within each year.


Ask Yourself These Questions / Perform These Checks

  • Is the number of customers I'm currently forecasting an unreasonable amount based on my total addressable market?

    • Example, if there's only 100 possible customers and I'm showing 10,000 customers in year 2 then I need to lower my assumptions to decrease the number of expected customers.

  • Click over into Revenue Streams and determine if you're bringing in too much revenue in the current year or if you're growing at more than 3X year over year in any of your years shown.

    • If revenue is too large in the current year or growing too quickly you'll need to lower the number of customers you bring in by adjusting either your assumptions or conversion rates. The same is true for the inverse, if you're not earning enough revenue, then you'll need to bring in more customers by adjusting either your conversion rates or the assumptions you've made.

  • Finally, now that the revenue forecast is reasonable / attractive and the number of customers has been verified to be appropriate, you need to make sure that your strategies are accurate from a standpoint of effectiveness. This means making sure the majority of your customers come from your (expectedly) most important strategies.

    • Because you already know how many customers you need this is simply making sure that, if you believe "partnerships" will be your biggest strategy followed by affiliates and influencers that these strategies are showing as bringing in the largest share of customers in the order of biggest to smallest that you expect.


Using Customer Acquisition Month to Month After Onboarding

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