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• Streaming client over TCP and RTSP through Wi-Fi or LAN in Android

  6 janvier 2015, par Gowtham

  I am struggling to develop streaming client for DVR camera’s, I tried with VLC Media player through RTSP protocol I got the solution (used Wi-Fi standard model like, Netgear etc.,), but the same code is not supporting for other Wi-Fi Modem’s, now am working with FFMPEG framework to implement the streaming client in android using JNI API. Not getting any proper idea to implement JNI api

  Network Camera working with IP Cam Viewer App

  code below,

  /*****************************************************/
  
  /* functional call */
  
  /*****************************************************/
  
  
  
  jboolean Java_FFmpeg_allocateBuffer( JNIEnv* env, jobject thiz )
  
  {
  
  
  
      // Allocate an AVFrame structure
  
      pFrameRGB=avcodec_alloc_frame();
  
      if(pFrameRGB==NULL)
  
          return 0;
  
  sprintf(debugMsg, "%d %d", screenWidth, screenHeight);
  
  INFO(debugMsg);
  
      // Determine required buffer size and allocate buffer
  
      numBytes=avpicture_get_size(dstFmt, screenWidth, screenHeight);
  
  /*
  
      numBytes=avpicture_get_size(dstFmt, pCodecCtx->width,
  
                    pCodecCtx->height);
  
  */
  
      buffer=(uint8_t *)av_malloc(numBytes * sizeof(uint8_t));
  
  
  
      // Assign appropriate parts of buffer to image planes in pFrameRGB
  
      // Note that pFrameRGB is an AVFrame, but AVFrame is a superset
  
      // of AVPicture
  
      avpicture_fill((AVPicture *)pFrameRGB, buffer, dstFmt, screenWidth, screenHeight);
  
  
  
      return 1;
  
  }
  
  
  
  
  
  /* for each decoded frame */
  
  jbyteArray Java_FFmpeg_getNextDecodedFrame( JNIEnv* env, jobject thiz )
  
  {
  
  
  
  
  
  av_free_packet(&packet);
  
  
  
  while(av_read_frame(pFormatCtx, &packet)>=0) {
  
  
  
      if(packet.stream_index==videoStream) {
  
  
  
          avcodec_decode_video2(pCodecCtx, pFrame, &frameFinished, &packet);
  
  
  
          if(frameFinished) {     
  
  
  
          img_convert_ctx = sws_getContext(pCodecCtx->width, pCodecCtx->height, pCodecCtx->pix_fmt, screenWidth, screenHeight, dstFmt, SWS_BICUBIC, NULL, NULL, NULL);
  
  
  
  /*
  
  img_convert_ctx = sws_getContext(pCodecCtx->width, pCodecCtx->height, pCodecCtx->pix_fmt, pCodecCtx->width, pCodecCtx->height, dstFmt, SWS_BICUBIC, NULL, NULL, NULL);
  
  */
  
  
  
          sws_scale(img_convert_ctx, (const uint8_t* const*)pFrame->data, pFrame->linesize,
  
       0, pCodecCtx->height, pFrameRGB->data, pFrameRGB->linesize);
  
  
  
  ++frameCount;
  
  
  
          /* uint8_t == unsigned 8 bits == jboolean */
  
          jbyteArray nativePixels = (*env)->NewByteArray(env, numBytes);
  
          (*env)->SetByteArrayRegion(env, nativePixels, 0, numBytes, buffer);
  
          return nativePixels;
  
          }
  
  
  
      }
  
  
  
      av_free_packet(&packet);
  
  }
  
  
  
  return NULL;
  
  }
  
  
  
  /*****************************************************/
  
  /* / functional call */
  
  /*****************************************************/
  
  
  
  
  
  jstring
  
  Java_FFmpeg_play( JNIEnv* env, jobject thiz, jstring jfilePath )
  
  {
  
      INFO("--- Play");
  
  char* filePath = (char *)(*env)->GetStringUTFChars(env, jfilePath, NULL);
  
  RE(filePath);
  
  
  
  /*****************************************************/
  
  
  
    AVFormatContext *pFormatCtx;
  
    int             i, videoStream;
  
    AVCodecContext  *pCodecCtx;
  
    AVCodec         *pCodec;
  
    AVFrame         *pFrame; 
  
    AVPacket        packet;
  
    int             frameFinished;
  
    float           aspect_ratio;
  
    struct SwsContext *img_convert_ctx;
  
  
  
  INFO(filePath);
  
  
  
  /* FFmpeg */
  
  
  
    av_register_all();
  
  
  
    if(av_open_input_file(&pFormatCtx, filePath, NULL, 0, NULL)!=0)
  
      RE("failed av_open_input_file ");
  
  
  
    if(av_find_stream_info(pFormatCtx)<0)
  
          RE("failed av_find_stream_info");
  
  
  
    videoStream=-1;
  
    for(i=0; inb_streams; i++)
  
      if(pFormatCtx->streams[i]->codec->codec_type==AVMEDIA_TYPE_VIDEO) {
  
        videoStream=i;
  
        break;
  
      }
  
    if(videoStream==-1)
  
          RE("failed videostream == -1");
  
  
  
    pCodecCtx=pFormatCtx->streams[videoStream]->codec;
  
  
  
    pCodec=avcodec_find_decoder(pCodecCtx->codec_id);
  
    if(pCodec==NULL) {
  
      RE("Unsupported codec!");
  
    }
  
  
  
    if(avcodec_open(pCodecCtx, pCodec)<0)
  
      RE("failed codec_open");
  
  
  
    pFrame=avcodec_alloc_frame();
  
  
  
  /* /FFmpeg */
  
  
  
  INFO("codec name:");
  
  INFO(pCodec->name);
  
  INFO("Getting into stream decode:");
  
  
  
  /* video stream */
  
  
  
    i=0;
  
    while(av_read_frame(pFormatCtx, &packet)>=0) {
  
  
  
      if(packet.stream_index==videoStream) {
  
        avcodec_decode_video2(pCodecCtx, pFrame, &frameFinished, &packet);
  
        if(frameFinished) {
  
  ++i;
  
  INFO("frame finished");
  
  
  
      AVPicture pict;
  
  /*
  
      img_convert_ctx = sws_getContext(pCodecCtx->width, pCodecCtx->height,
  
   pCodecCtx->pix_fmt, pCodecCtx->width, pCodecCtx->height,
  
   PIX_FMT_YUV420P, SWS_BICUBIC, NULL, NULL, NULL);
  
  
  
      sws_scale(img_convert_ctx, (const uint8_t* const*)pFrame->data, pFrame->linesize,
  
   0, pCodecCtx->height, pict.data, pict.linesize);
  
  */
  
        }
  
      }
  
      av_free_packet(&packet);
  
    }
  
  
  
  /* /video stream */
  
  
  
    av_free(pFrame);
  
  
  
    avcodec_close(pCodecCtx);
  
  
  
    av_close_input_file(pFormatCtx);
  
  
  
    RE("end of main");
  
  }

  I can’t able to get the frames from Network camera

  And give some idea to implement the live stream client for DVR camera in Android

• How to Implement Cross-Channel Analytics : A Guide for Marketers

  17 avril 2024, par Erin

  Every modern marketer knows they have to connect with consumers across several channels. But do you know how well Instagram works alongside organic traffic or your email list ? Are you even tracking the impacts of these channels in one place ?

  You need a cross-channel analytics solution if you answered no to either of these questions. 

  In this article, we’ll explain cross-channel analytics, why your company probably needs it and how to set up a cross-channel analytics solution as quickly and easily as possible.

  What is cross-channel analytics ? 

  Cross-channel analytics is a form of marketing analytics that collects and analyses data from every channel and campaign you use.

  The result is a comprehensive view of your customer’s journey and each channel’s role in converting customers. 

  Cross-channel analytics lets you track every channel you use to convert customers, including :

  • Your website
  • Social media profiles
  • Email
  • Paid search
  • E-commerce
  • Retargeting campaigns

  Cross-channel analytics solves one of the most significant issues of cross-channel or multi-channel marketing efforts : measurement. 

  Research shows that only 16% of marketing tech stacks allow for accurate measurement of multi-channel initiatives across channels. 

  That’s a problem, given the staggering number of touchpoints in a typical buyer’s conversion path. However, it can be fixed using a cross-channel analytics approach that lets you measure the performance of every channel and assign a dollar value to its role in every conversion. 

  The difference between cross-channel analytics and multi-channel analytics

  Cross-channel analytics and multi-channel analytics sound very similar, but there’s one key difference you need to know. Multi-channel analytics measures the performance of several channels, but not necessarily all of them, nor the extent to which they work together to drive conversions. Conversely, cross-channel analytics measures the performance of all your marketing channels and how they work together. 

  What are the benefits of cross-channel analytics 

  Cross-channel analytics offers a lot of marketing and business benefits. Here are the ones marketing managers love most.

  Get a complete view of the customer journey

  Implementing a cross-channel analytics solution is the only way to get a complete view of your customer journey. 

  Cross-channel marketing analytics lets you see your customer journey in high definition, allowing you to build comprehensive customer profiles using data from multiple sources across every touchpoint. 

  

  The result ? You get to understand how every customer behaves at every point of the customer journey, why they convert or leave your funnel, and which channels play the biggest role. 

  In short, you get to see why customers convert so you can learn how to convert more of them.

  Personalise the customer experience

  According to a McKinsey study, customers demand personalisation, and brands that excel at it generate 40% more revenue. Deliver the personalisation they desire and reap the benefits with cross-channel analytics. 

  When you understand the customer journey in detail, it becomes much easier to personalise your website and marketing efforts to their preferences and behaviours.

  Identify your most effective marketing channels

  Cross-channel marketing helps you understand your marketing efforts to see how every channel impacts conversions. 

  Take a look at the screenshot from Matomo below. Cross-channel analytics lets you get incredibly granular — we can see the number of conversions of organic search drives and the performance of individual search engines. 

  

  This makes it easy to identify your most effective marketing channels and allocate your resources appropriately. It also allows you to ask (and answer) which channels are the most effective.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Attribute conversions accurately 

  An attribution model decides how you assign credit for each customer conversion to different touchpoints on the customer journey. Without a cross-channel analytics solution, you’re stuck using a standard attribution model like first or last click. 

  These models will show you how customers first found your brand or which channel finally convinced them to convert, but it doesn’t help you understand the role all your channels played in the conversion. 

  Cross-channel analytics solves this attribution problem. Rather than attributing a conversion to the touchpoint that directly led to the sale, cross-channel data gives you the real picture and allows you to use multi-touch attribution to understand which touchpoints generate the most revenue.

  How to set up cross-channel analytics

  Now that you know what cross-channel analytics is and why you should use it, here’s how to set up your solution. 

  1. Determine your objectives

  Defining your marketing goals will help you build a more relevant and actionable cross-channel analytics solution. 

  If you want to improve marketing attribution, for example, you can choose a platform with that feature built-in. If you care about personalisation, you could choose a platform with A/B testing capabilities to measure the impact of your personalisation efforts. 

  1. Set relevant KPIs

  You’ll want to track relevant KPIs to measure the marketing effectiveness of each channel. Put top-of-the-funnel metrics aside and focus on conversion metrics. 

  These include :

  • Conversion rate
  • Average visit duration
  • Bounce rate

  1. Implement tracking and analytics tools

  Gathering customer data from every channel and centralising it in a single location is one of the biggest challenges of cross-channel analytics. Still, it’s made easier with the right tracking tool or analytics platform. 

  The trick is to choose a platform that lets you measure as many of your channels as possible in a single platform. With Matomo, for example, you can track search, paid search, social and email campaigns and your website analytics.

  1. Set up a multi-touch attribution model

  Now that you have all of your data in one place, you can set up a multi-touch attribution model that lets you understand the extent to which each marketing channel contributes to your overall success. 

  There are several attribution models to choose from, including :

  

  Each model has benefits and drawbacks, so choosing the right model for your organisation can be tricky. Rather than take a wild guess, evaluate each model against your marketing objectives, sales length cycle and data availability.

  For example, if you want to focus on optimising customer acquisition costs, a model that prioritises earlier touchpoints will be better. If you care about conversions, you might try a time decay model. 

  1. Turn data into insights with reports

  One of the big benefits of choosing a tool like Matomo, which consolidates data in one place, is that it significantly speeds up and simplifies reporting.

  When all the data is stored in one platform, you don’t need to spend hours combing through your social media platforms and copying and pasting analytics data into a spreadsheet. It’s all there and ready for you to run reports.

  Try Matomo for Free

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

  Start for free

  No credit card required

  1. Take action

  There’s no point implementing a cross-channel analytics system if you aren’t going to take action. 

  But where should you start ?

  Optimising your budgets and prioritising marketing spend is a great starting point. Use your cross-channel insights to find your most effective marketing channels (they’re the ones that convert the most customers or have the highest ROI) and allocate more of your budget to them. 

  You can also optimise the channels that aren’t pulling their weight if social media is letting you down ; for example, experiment with tactics like social commerce that could drive more conversions. Alternatively, you could choose to stop investing entirely in these channels.

  Cross-channel analytics best practices

  If you already have a cross-channel analytics solution, take things to the next level with the following best practices. 

  Use a centralised solution to track everything

  Centralising your data in one analytics tool can streamline your marketing efforts and help you stay on top of your data. It won’t just save you from tabbing between different browsers or copying and pasting everything into a spreadsheet, but it can also make it easier to create reports. 

  Think about consumer privacy 

  If you are looking at a new cross-channel analytics tool, consider how it accounts for data privacy regulations in your area. 

  You’re going to be collecting a lot of data, so it’s important to respect their privacy wishes. 

  It’s best to choose a platform like Matomo that complies with the strictest privacy laws (CCPA, GDPR, etc.).

  Monitor data in real time

  So, you’ve got a holistic view of your marketing efforts by integrating all your channels into a single tool ?

  Great, now go further by monitoring the impact of your marketing efforts in real time.

  

  With a web analytics platform like Matomo, you can see who visits your site, what they do, and where they come from through features like the visits log report, which even lets you view individual user sessions. This lets you measure the impact of posting on a particular social channel or launching a new offer. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  Reallocate marketing budgets based on performance

  When you track every channel, you can use a multi-touch attribution model like position-based or time-decay to give every channel the credit it deserves. But don’t just credit each channel ; turn your valuable insights into action. 

  Use cross-channel attribution analytics data to reallocate your marketing budget to the most profitable channels or spend time optimising the channels that aren’t pulling their weight. 

  Cross-channel analytics platforms to get started with 

  The marketing analytics market is huge. Mordor Intelligence valued it at $6.31 billion in 2024 and expects it to reach $11.54 billion by 2029. Many of these platforms offer cross-channel analytics, but few can track the impact of multiple marketing channels in one place. 

  So, rather than force you to trawl through confusing product pages, we’ve shortlisted three of the best cross-channel analytics solutions. 

  Matomo

  

  Matomo is a web analytics platform that lets you collect and centralise your marketing data while giving you 100% accurate data. That includes search, social, e-commerce, campaign tracking data and comprehensive website analytics.

  Better still, you get the necessary tools to turn those insights into action. Custom reporting lets you track and visualise the metrics that matter, while conversion optimisation tools like built-in A/B testing, heatmaps, session recordings and more let you test your theories. 

  Google Analytics

  

  Google Analytics is the most popular and widely used tool on the market. The level of analysis and customisation you can do with it is impressive for a free tool. That includes tracking just about any event and creating reports from scratch. 

  Google Analytics provides some cross-channel marketing features and lets you track the impact of various channels, such as social and search, but there are a couple of drawbacks. 

  Privacy can be a concern because Google Analytics collects data from your customers for its own remarketing purposes. 

  It also uses data sampling to generate wider insights from a small subset of your data. This lack of accurate data reporting can cause you to generate false insights.

  With Google Analytics, you’ll also need to subscribe to additional tools to gain advanced insights into the user experience. So, consider that while this tool is free, you’ll need to pay for heatmaps, session recording and A/B testing tools to optimise effectively.

  Improvado

  

  Improvado is an analytics tool for sales and marketing teams that extracts thousands of metrics from hundreds of sources. It centralises data in data warehouses, from which you can create a range of marketing dashboards.

  While Improvado does have analytics capabilities, it is primarily an ETL (extraction, transform, load) tool for organisations that want to centralise all their data. That means marketers who aren’t familiar with data transformations may struggle to get their heads around the complexity of the platform.

  Make the most of cross-channel analytics with Matomo

  Cross-channel analytics is the only way to get a comprehensive view of your customer journey and understand how your channels work together to drive conversions.

  Then you’re dealing with so many channels and data ; keeping things as simple as possible is the key to success. That’s why over 1 million websites choose Matomo. 

  Our all-in-one analytics solution measures traditional web analytics, behavioural analytics, attribution and SEO, so you have 100% accurate data in one place. 

  Try it free for 21 days. No credit card required.

  Try Matomo for Free

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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.

  Try Matomo for Free

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

  Start for free

  No credit card required

  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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