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• Incrementality Testing : Quick-Start Guide (With Calculations)

  26 mars 2024, par Erin

  How do you know when a campaign is successful ? When you earn more revenue than last month ?

  Maybe.

  But how do you know how much of an impact a certain campaign or channel had on your sales ?

  With marketing attribution, you can determine credit for each sale.

  But if you want a deeper look, you need to understand the incremental impact of each channel and campaign.

  The way you do this ?

  Incrementality testing.

  In this guide, we break down what incrementality is, why it’s important and how to test it so you can double down on the activities driving the most growth.

  What is incrementality ?

  So, what exactly is incrementality ?

  Let’s say you just ran a marketing campaign for a new product. The launch was a success. Breakthrough numbers in your revenue. You used a variety of channels and activities to bring it all together.

  So, you launch a plan for next month’s campaign. But you don’t truly know what moved the needle.

  Did you just hit new highs because your audience is bigger ? And your brand is greater ?

  Or did the recent moves you made make a direct difference ?

  This is incrementality.

  

  Incrementality is growth directly attributed to marketing efforts beyond the overall impact of your brand. By measuring and conducting incrementality testing, you can clearly see how much of a difference each activity or channel truly impacted business growth. 

  What is incrementality testing ?

  Incrementality testing allows marketers to gauge the effectiveness of a marketing tactic or strategy. It tells you if a particular marketing activity had a positive, negative or neutral impact on your business. 

  It also tells you the overall impact it can have on your key performance indicators (KPIs). 

  The result ?

  You can pinpoint the highest-performing moves and incorporate them into your marketing workflows. You also discard marketing strategies with negligible, neutral or even negative impacts. 

  For example, let’s say you think a B2B LinkedIn ads campaign will help you reach your product launch goals. An incrementality test can tell you if the introduction of this campaign will help you get to the desired outcome.

  How incrementality testing works

  Before diving into your testing phase, you must clearly identify your KPIs.

  Here are the top KPIs you should be tracking on your website :

  • Ad impressions
  • Website visits
  • Leads
  • Sales

  The exact KPIs will depend on your marketing goals. You’re ready to move forward once you know your key performance indicators.

  Here’s how incrementality testing works step-by-step :

  1. Define a test and control group

  The first step is to define a test group and control group. 

  • A test group is a segment of your target audience that’s exposed to the marketing campaign. 
  • A control group is a segment that isn’t. 

  Keep in mind that both groups have similar demographics and other relevant characteristics. 

  2. Execute your campaign

  The second step is to run the marketing campaign on the test group. This can be a Facebook ad, LinkedIn ad or email marketing campaign.

  It all depends on your goals and your primary channels.

  3. Measure outcomes

  The third step is to measure the campaign’s impact based on your KPIs. 

  Let’s say a brand wants to see if a certain marketing move increases its leads. The test can tell them the number of email sign-ups with and without the campaign. 

  4. Compare results

  Next, compare the test group results with the control group. The difference in outcomes tells you the impact of that campaign. You can then use this difference to inform your future marketing strategies. 

  With Matomo, you can easily track results from campaigns — like conversions. 

  Our platform lets you quickly see what channels are getting the best results so you can gain insights into incrementality and optimise your strategy.

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  Get the web insights you need, without compromising data accuracy.

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  Why it’s important to conduct incrementality tests

  The digital marketing industry is constantly changing. Marketers need to stay on their toes to keep up. Incrementality tests help you stay on track.

  For example, let’s say you’re selling laptops. You can increase your warranty period to three years to see the impact on sales. An incrementality test will tell you if this move will boost your sales (and by how much).

  Now, let’s dive into the reasons why you need to consistently conduct incrementality tests :

  Determine the right tactics for success

  Identifying the best action to grow your business is a challenge every marketer faces.

  The best way to identify marketing tactics is by conducting incrementality testing. These tactics are bound to work since data back them. As a result, you can optimise your marketing budget and maximise your ROIs. 

  It lets you run multiple tests to identify the most impactful strategy between :

  • An email marketing strategy
  • A social media strategy 
  • A PPC ad

  For instance, an incrementality test might suggest email marketing will be more cost-effective than an ad campaign. What you can do is :

  • Expose the test group to the email marketing campaign and then compare the results with the control group
  • Expose the test group to the ad campaign and then compare its results with the control group

  Then, you can calculate the difference in results between the two marketing campaigns. This lets you focus on the strategy with a better ROI or ROAS potential. 

  Accurate data

  Marketing data is powerful. But getting accurate data can be challenging. With incrementality testing, you get to know the true impact of a marketing campaign. 

  Plus, with this testing strategy, you don’t have to waste your marketing budget. 

  With Matomo, you get 100% accurate data on all website activities. 

  Unlike Google Analytics, Matomo doesn’t rely on inaccurate data sampling — limiting the amount of data analysed.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Get the most out of your marketing investment

  Every business owner wants to maximise their return on investment. The ROI you get mainly depends on the marketing strategy. 

  For instance, email marketing offers an ROI of about 40:1 with some sources even reporting as high as 72:1.

  Incrementality testing helps you make informed investment decisions. With it, you can pinpoint the tactics that are most likely to bring the highest return. You can then focus your resources on them. It also helps you stay away from low-performing strategies. 

  Increase revenue

  It’s safe to say that the goal behind every marketing effort is a revenue boost. The higher your revenue, the more profits you generate. However, for many marketers, it’s an uphill battle. 

  With incrementality testing, you can boost your revenue by focusing your efforts in the right direction. 

  Get more traffic

  Incrementality testing tells you if a particular strategy can help you drive more traffic. You can use it to get more high-quality leads to your website or landing pages and double down on high-traffic strategies to increase those leads.

  How to test incrementality

  

  Developing an implementation plan is crucial to generate accurate insights from an incrementality test. Incrementality testing is like running a science experience. You need to go through several stages. Each stage is important for generating accurate results. 

  Here’s how you test incrementality :

  Define your goals

  Get clarity on what you want to achieve with this campaign. Which KPIs do you want to test ? Is it the return on your overall investment (ROI), return on ad spend (ROAS) or something else ?

  Segment your audience

  Selecting the right audience segment is crucial to getting accurate insights with an incrementality test. Decide the demographics and psychographics of the audience you want to target. Then, divide this audience segment into two sub-parts :

  • Test group (people you’ll expose to the marketing campaign)
  • Control group (people who won’t be exposed to the campaign)

  These groups are a part of the larger segment. This means people in both groups will have similar attributes. 

  Launch the test at the right time

  Before the launch, decide on the length of the test. Ideally, it should be at least one week. Don’t run any other campaigns in this window, as it can interfere with the results. 

  Analyse the data and take action

  Once the campaign is over, measure the results from both groups. Compare the data to identify incremental lift in your selected KPIs. 

  Let’s say you want to see if this campaign can boost your sales. Check to see if the test group responded differently than the control group. If the sales equal your desired outcome, you have a winning strategy. 

  Not all incrementality tests result in a positive incremental lift ; Some can be neutral, indicating that the campaign didn’t have any effect. Some can even indicate a negative lift, which means your core group performed better than the test group. 

  Lastly, take action based on the test findings. 

  Incrementality test examples 

  You can use incrementality testing to identify gaps and growth opportunities in your strategy. 

  Here’s an example :

  Let’s say a company runs an incrementality test on a YouTube marketing strategy for sales. The results indicate that the ROI was only $0.10, as the company makes $1.10 for every $1.00 spent. This alarms the marketing department and helps them optimise the campaign for a higher ROI. 

  Here’s another practical example :

  Let’s say a retail business wanted to test the effectiveness of its ad campaign. So, the retailer optimises its ad campaign after conducting an incrementality test on a test and control group. As a result, they experienced a 34% incremental increase in sales.

  How to calculate incrementality in marketing

  Once you’ve aggregated the data, it’s time to calculate. There are two ways to calculate incrementality :

  Incremental profit 

  The first one is incremental profit. It tells you how much profit you can generate with a strategy (If any). With it, you get the actual value of a marketing campaign. 

  It’s calculated with the following formula :

  Test group profit – control group profit = incremental profit 

  For example, let’s say you’re exposing a test group to a paid ads campaign. And it generates a profit of $3,000. On the other hand, the control group generated a $2,000 profit. 

  In this case, your incremental profit will be $1,000 ($3,000 – $2,000). 

  However, if the paid ads campaign generates a $2,000 profit, the incremental profit would be zero. Essentially, you’re generating the same profit as before, which means the campaign doesn’t work. Similarly, a marketing strategy is no good if it generates lower profits than the control group. 

  Incremental lift

  Incremental lift measures the difference in the conversions you generate with each group. 

  Here’s the formula :

  (Test – Control)/Control x 100 = Lift

  So, let’s say the test group and control group generated 2,000 and 1,000 conversions, respectively. 

  The incremental lift you’ll get from this incrementality test would be :

  (2,000 – 1,000)/1,000 x 100 = 100

  This turns out to be a 100% incremental lift.

  How to track incrementality with Matomo

  Incrementality testing lets you use a practical approach to identify the best marketing path for your business.

  It helps you develop a hyper-focused approach that gives you access to accurate and practical data. 

  With these insights, you can confidently move forward to maximise your ROI since it helps you focus on high-performing tactics. 

  The result is more revenue and profit for your business. 

  Plus, all you need to do is identify your target audience, divide them into two groups and run your test. Then, the results will be compared to determine if the marketing strategy offers any value. 

  Conducting incrementality tests may take time and expertise. 

  But, thanks to Matomo, you can leverage accurate insights for your incrementality tests to ensure you make the right decisions to grow your business.

  See for yourself why over 1 million websites choose Matomo. Try it free for 21-days now. No credit card required.

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• Diagonal Split using ffmpeg

  8 juillet 2017, par Jeffin

  I am trying to acheive the following effect using ffmpeg

  

  I have tried multiple options , but failed so far,

  I have referred the following questions , not happening for me

  • FFmpeg : Add alpha channel to a video using a PNG mask
  • FFMPEG Crop with side by side merge
  • https://superuser.com/questions/916431/ffmpeg-filter-to-boxblur-and-greyscale-a-video-using-alpha-mask?rq=1

  I have three videos but i have somewhat acheived the diagonal split for two videos using the following code , but still couldnt get the output for three videos or four

  ffmpeg -i input0 -i input1 -filter_complex \
  
  "[1:v][0:v]blend=all_expr=if(gt(X\,Y*(W/H))\,A\,B)" output

• FFmpeg - Rotating at angle

  23 septembre 2017, par connor

  I’ve been working through FFmpeg, but I have been unable to get a rotation to run from the examples they have on their site. I am trying to "wiggle" a video back and forth at a fixed point on the bottom - think a head moving left to right (and so on).

  I am attempting to do this with the filter "rotate" (https://ffmpeg.org/ffmpeg-filters.html#rotate). Attempting to use their examples, I get an error.

  This is what I have so far :

  ffmpeg -i vid1.mp4 -i vid2.mov -loop 1 -i image.png -filter_complex "\
  
      [2:v]alphaextract, scale=240x160[mask];\
  
      [0:v] scale=240x160, rotate=A*sin(2*PI/T*t) [ascaled];\
  
      [ascaled][mask]alphamerge[masked];\
  
      [1:v]scale=480x360[background];\
  
      [background][masked]overlay=120:20"\
  
      -c:a copy 65B6354F61B4AF02_HD_sq.MOV

  I am using "rotate" directly from an example in an attempt to get something to run at all.

  The error I get back is :

  [Parsed_rotate_3 @ 0x7ff4476045e0] [Eval @ 0x7fff5b3e3f00] Undefined constant or missing '(' in 'T*t)'
  
  [Parsed_rotate_3 @ 0x7ff4476045e0] Error occurred parsing angle expression 'A*sin(2*PI/T*t)'
  
  [Parsed_rotate_3 @ 0x7ff4476045e0] Failed to configure output pad on Parsed_rotate_3
  
  Error reinitializing filters!
  
  Failed to inject frame into filter network: Invalid argument
  
  Error while processing the decoded data for stream #1:0

  If I remove ’A’, ’T’, ’sin’, etc, rotate does actually work, but far from the desired behavior.

  Am I missing something to expose those params ?