If you’re anything like me, ideating and building strategies is often much more fun than presenting your plan and being pressed by the question, “what am I going to get from this? How much more revenue (or conversion volume) is this initiative going to provide?”
Last year, we talked about forecasting uncertainty in Excel as one way to answer that question. Rachael Law also taught us how to identify budget increase opportunities in Search using impression share metrics. Today, we’ll go through two approaches to forecast spend and conversion potential specifically for paid social campaigns.
Scenario A: Launching a New Campaign, Channel or Platform
Launching a new
campaign or expanding into a new platform can be intimidating. It’s impossible
to predict exactly what how much volume or what kind of quality you’ll get out
of the ad dollars you invest. However, we can leverage historical data from an
aggregation of other advertisers (read: benchmarks!) to create a reasonable
Step 1: Gather the Data
To create a forecast using benchmark data, you will first need to find one cost metric (avg. CPC or avg. CPM), and one engagement metric (avg. CTR).
If you are launching a new campaign in an existing channel, pull the historical data for a set of campaigns most similar to your proposal (e.g. if you are proposing a Conversions campaign targeting the U.S., look at all previous Conversions campaigns targeting the U.S.). Certainly, there will be differences between your previous campaign and the future one, but this will give you a reasonable approximation for what you might expect.
If you are launching a campaign in a new channel with no historical data, you can do a quick Google search for the benchmarks of that platform. You can find industry-specific benchmark data for Facebook on a number of different blogs, including WordStream and Instapage. Each quarter, AdStage also releases a paid media benchmark report that includes cost and engagement metrics for Facebook, Instagram, LinkedIn, Twitter and YouTube.
The final metric you will need to pull is your own website conversion rate. Channel-specific post-click conversion rates are ideal, but you can use the overall website conversion rate as a substitute if planning to launch on a new ad platform. Some sources from the previous step will also provide benchmark conversion rates, which you can blend with your own website data (take an average of the two, or some other weighted average that makes sense for your goals).
Step 2: Calculate the Outcomes
Once you have
these foundational metrics identified, you can set up some simply marketing
math in Excel or Google Sheets to translate a dollar amount (budget
recommendation) into the volume of impressions, clicks, and conversions that
can be expected.
Scenario B: Quantifying the Growth Potential of Existing Campaigns
In another circumstance, you might
find yourself wondering whether your current campaigns (particularly ones that
are performing well) have the potential to utilize more budget than they
presently are. In Search and Display, we have impression share metrics that
make such calculations simply. On the social side, not so much.
Fear not! We’ve gone through the trouble of creating an organic growth forecasting tool that you can copy for free here.
To use this tool, you’ll need to
follow the below steps:
- Step 1: Copy the tool into your own Google Drive account. You can do this by selecting File >> Make a Copy and selecting the destination and file name.
- Step 2: Download the Spend, Impression, and Conversion data for the campaigns or ad sets you want to include in the forecast.
- Step 3: Copy and paste ONLY the campaign/ad set names, spend, impressions, and conversions columns into the spreadsheet (cells A8:D225).
- Step 4: Update the number of days contained in your data (cell E4).
- Step 5: Update the Target Frequency, or the maximum number of times each month that you would like a user to see one of your ads (cell B2).
- Step 6: Insert the Estimated Audience Size from the ad platform for each campaign or ad set (cells E8:E225).
- Step 7: View the growth potential in the cells highlighted in green. You can adjust the Target Frequency to assess how different levels of saturation would affect your total spend potential.
A Word of Caution
As with all statistical modeling and forecasting efforts, the outputs from these exercises should be treated as predictions rather than promises. They are calculations based on actual circumstances in the recent past but are not a guarantee of similar conditions persisting in the future. However, with that distinction clearly understood, these forecasts can be a powerful tool to identify and communicate opportunities for growth