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• 7 Benefits Segmentation Examples + How to Get Started

  26 mars 2024, par Erin

  Every copywriter knows the importance of selling a product’s benefits, not its features. So why should your marketing efforts be different ?

  Answer : they shouldn’t.

  It’s time to stop using demographic or behavioural traits to group customers and start using benefits segmentation instead.

  Benefits segmentation groups your customers based on the value they get from your product or service. In this article, we’ll cover seven real-life examples of benefits segmentation, explain why it’s so powerful and show how to get started today.

  What is benefits segmentation ?

  Benefits segmentation is a way for marketers to group their target market based on the value they get from their products or services. It is a form of customer segment marketing. Other types of market segmentation include :

  • Geographic segmentation
  • Demographic segmentation
  • Psychographic segmentation
  • Behavioural segmentation
  • Firmographic segmentation

  Customers could be the same age, from the same industry and live in the same location but want drastically different things from the same product. Some may like the design of your products, others the function, and still more the price. 

  Whatever the benefits, you can make your marketing more effective by building advertising campaigns around them.

  Why use benefits segmentation ?

  Appealing to the perceived benefits of your product is a powerful marketing strategy. Here are the advantages of you benefit segmentation can expect :

  

  More effective marketing campaigns

  Identifying different benefits segments lets you create much more targeted marketing campaigns. Rather than appeal to a broad customer base, you can create specific ads and campaigns that speak to a small part of your target audience. 

  These campaigns tend to be much more powerful. Benefits-focused messaging better resonates with your audience, making potential customers more likely to convert.

  Better customer experience 

  Customers use your products for a reason. By showing you understand their needs through benefits segmentation, you deliver a much better customer experience — in terms of messaging and how you develop new products. 

  In today’s world, experience matters. 80% of customers say a company’s experience is as important as its products and services.

  Stronger customer loyalty

  When products or services are highly targeted at potential customers, they are more likely to return. More than one-third (36%) of customers would return to a brand if they had a positive experience, even if cheaper or more convenient alternatives exist.

  Using benefits segmentation will also help you attract the right kind of people in the first place — people who will become long-term customers because your benefits align with their needs. 

  Improved products and services

  Benefits segmentation makes it easier to tailor products or services to your audiences’ wants and needs. 

  Rather than creating a product meant to appeal to everyone but doesn’t fulfil a real need, your team can create different ranges of the same product that target different benefits segments. 

  Higher conversion rates

  Personalising your pitch to individual customers is powerful. It drives performance and creates better outcomes for your target customer. Companies that grow faster drive 40 per cent more revenue from personalisation than their slower-growing counterparts.

  When sales reps understand your product’s benefits, talking to customers about them and demonstrating how the product solves particular pain points is much easier. 

  In short, benefits segmentation can lead to higher conversion rates and a better return on investment. 

  7 examples of benefits segmentation

  Let’s take a look at seven examples of real-life benefits segmentation to improve your understanding :

  Nectar

  Mattress manufacturer Nectar does a great job segmenting their product range by customer benefits. That’s a good thing, given how many different things people want from their mattress. 

  It’s not just a case of targeting back sleepers vs. side sleepers ; they focus on more specific benefits like support and cooling. 

  

  Take a look at the screenshot above. Nectar mentions the benefits of each mattress in multiple places, making it easy for customers to find the perfect mattress. If you care about value, for example, you might choose “The Nectar.” If pressure relief and cooling are important to you, you might pick the “Nectar Premier.”

  24 Hour Fitness

  A gym is a gym is a gym, right ? Not when people use it to achieve different goals, it’s not. And that’s what 24 Hour Fitness exploits when they sell memberships to their audience. 

  As you can see from its sales page, 24 Hour Fitness targets the benefits that different customers get from their products :

  

  Customers who just care about getting access to weights and treadmills for as cheap as possible can buy the Silver Membership. 

  But getting fit isn’t the only reason people go to the gym. That’s why 24 Hour Fitness targets its Gold Membership to those who want the “camaraderie” of studio classes led by “expert instructors.”

  Finally, some people value being able to access any club, anywhere in the country. Consumers value flexibility greatly, so 24 Hour Fitness limits this perk to its top-tier membership. 

  Notion

  Notion is an all-in-one productivity and note-taking app that aims to be the only productivity tool people and teams need. Trying to be everything to all people rarely works, however, which is why Notion cleverly tweaks its offering to appeal to the desires of different customer segments :

  

  For price-conscious individuals, it provides a pared solution that doesn’t bloat the user experience with features or benefits these consumers don’t care about.

  The Plus tier is the standard offering for teams who need a way to collaborate online. Still, there are two additional tiers for businesses that target specific benefits only certain teams need. 

  For teams that benefit from a longer history or additional functionality like a bulk export, Notion offers the Business tier at almost double the price of the standard Plus tier. Finally, the Enterprise tier for businesses requires much more advanced security features. 

  Apple

  Apple is another example of a brand that designs and markets products to customers based on specific benefits.

  

  Why doesn’t Apple just make one really good laptop ? Because customers want different things from them. Some want the lightest or smallest laptop possible. Others need ones with higher processing power or larger screens.

  One product can’t possibly deliver all those benefits. So, by understanding the precise reasons people need a laptop, Apple can create and market products around the benefits that are most likely to be sold. 

  Tesla

  In the same way Apple understands that consumers need different things from their laptops, Tesla understands that consumers derive different benefits from their cars. 

  It’s why the company sells four cars (and now a truck) that cover various sizes, top speeds, price points and more. 

  

  Tesla even asks customers about the benefits they want from their car when helping them to choose a vehicle. By asking customers to pick how they will use their new vehicle, Tesla can ensure the car’s benefits match up to the consumers’ goals. 

  Dynamite Brands

  Dynamite Brands is a multi-brand, community-based business that targets remote entrepreneurs around the globe. But even this heavily niched-down business still needs to create benefit segments to serve its audience better. 

  It’s why the company has built several different brands instead of trying to serve every customer under a single banner :

  

  If you just want to meet other like-minded entrepreneurs, you can join the Dynamite Circle, for example. But DC Black might be a better choice if you care more about networking and growing your business.

  It’s the same with the two recruiting brands. Dynamite Jobs targets companies that just want access to a large talent pool. Remote First Recruiting targets businesses that benefit from a more hands-on approach to hiring where a partner does the bulk of the work.

  Garmin

  Do you want your watch to tell the time or do you want it to do more ? If you fall into the latter category, Garmin has designed dozens of watches that target various benefits.

  

  Do you want a watch that tracks your fitness without looking ugly ? Buy the Venu. 

  Want a watch designed for runners ? Buy the Forerunner. 

  Do you need a watch that can keep pace with your outdoor lifestyle ? Buy the Instinct. 

  Just like Apple, Garmin can’t possibly design a single watch that delivers all these benefits. Instead, each watch is carefully built for the target customer’s needs. Yes, it makes the target market smaller, but it makes the product more appealing to those who care about those benefits.

  How to get started with benefits segmentation

  According to Gartner, 63% of digital marketing leaders struggle with personalisation. Don’t be one of them. Here’s how you can improve your personalisation efforts using benefits segmentation. 

  Research and define benefits

  The first step to getting started with benefit segmentation is understanding all the benefits customers get from your products. 

  You probably already know some of the benefits, but don’t underestimate the importance of customer research. Hold focus groups, survey customers and read customer reviews to discover what customers love about your products. 

  Create benefit-focused customer personas

  Now you understand the benefits, it’s time to create customer personas that reflect them. Group consumers who like similar benefits and see if they have any other similarities. 

  Price-conscious consumers may be younger. Maybe people who care about performance have a certain type of job. The more you can do to flesh out what the average benefits-focused consumer looks like, the easier it will be to create campaigns. 

  Create campaigns focused on each benefit

  Now, we get to the fun part. Make the benefit-focused customer personas you created in the last step the focus of your marketing campaigns going forward. 

  Don’t try to appeal to everyone. Just make your campaigns appeal to these people.

  Go deeper with segmentation analytics

  The quality of your benefit segmentation strategy hinges on the quality of your data. That’s why using a an accurate web analytics solution like Matomo to track how each segment behaves online using segmentation analytics is important.

  

  This data can make your marketing campaigns more targeted and effective.

  Benefits segmentation in practice

  Let’s say you have an e-commerce website selling a wide range of household items, and you want to create a benefit segment for “Tech Enthusiasts” who are interested in the latest gadgets and cutting-edge technology. You want to track and analyse their behaviour separately to tailor marketing campaigns or website content specifically for this group.

  1. Identify characteristics : Determine key characteristics or behaviours that define the “Tech Enthusiasts” segment. 

  This might include frequent visits to product pages of the latest tech products, site searches that contain different tech product names, engaging with tech-specific content in emails or spending more time on technology-related blog posts.

  One quick and surefire way to identify characteristics of a segment is to look historically at specific tech product purchases in your Matomo and work your way backwards to find out what steps a “Tech Enthusiast” takes before making a purchase. For instance, you might look at User Flows to discover this.

  

  2. Create segments in Matomo : Using Matomo’s segmentation features, you can create a segment that includes users exhibiting these characteristics. For instance :

  • • Segment by page visits : Create a segment that includes users who visited tech product pages or spent time on tech blogs.

  

  • • Segment by event tracking : If you’ve set up event tracking for specific actions (like clicking on “New Tech” category buttons), create a segment based on these events.
    • Combine conditions : Combine various conditions (e.g., pages visited, time spent, specific actions taken) to create a comprehensive segment that accurately represents “Tech Enthusiasts.”

  3. Track and analyse : Apply this segment to your analytics data in Matomo to track and analyse the behaviour of this group separately. Monitor metrics like their conversion rates, time spent on site or specific products they engage with.
  4. Tailor marketing : Use the insights from analysing this segment to tailor marketing strategies. This could involve creating targeted campaigns or customising website content to cater specifically to these users.

  Remember, the key is to define criteria that accurately represent the segment you want to target, use Matomo’s segmentation tools to isolate this group, and effectively derive actionable insights to cater to their preferences or needs.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Track your segmentation efforts 

  Benefits segmentation is a fantastic way to improve your marketing. It can help you deliver a better customer experience, improve your product offering and help your sales reps close more deals. 

  Segmenting your audience with an analytics platform lets you go even deeper. But doing so in a privacy-sensitive way can be difficult. 

  That’s why over 1 million websites choose Matomo as their web analytics solution. Matomo provides exceptional segmentation capabilities while remaining 100% accurate and compliant with global privacy laws.

  Find out how Matomo’s insights can level up your marketing efforts with our 21-day free trial, no credit card required.

  Try Matomo for Free

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• Processing h264 video/audio stream

  1er mars 2024, par Dinamo

  I have separate audio and video streams from a camera that I'm trying to merge to a single file.

  


  Video processing

  


  I have JVT NAL sequence, H.264 video, main @ L 31 data, I had the frames separated and I appended (concat) the frames to one file.

  


  here is the ffprobe output of the data :

  


  ffprobe version 4.2.7-0ubuntu0.1 Copyright (c) 2007-2022 the FFmpeg developers
  built with gcc 9 (Ubuntu 9.4.0-1ubuntu1~20.04.1)
  configuration: --prefix=/usr --extra-version=0ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-nvenc --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
  libavutil      56. 31.100 / 56. 31.100
  libavcodec     58. 54.100 / 58. 54.100
  libavformat    58. 29.100 / 58. 29.100
  libavdevice    58.  8.100 / 58.  8.100
  libavfilter     7. 57.100 /  7. 57.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  5.100 /  5.  5.100
  libswresample   3.  5.100 /  3.  5.100
  libpostproc    55.  5.100 / 55.  5.100
Input #0, h264, from 'frame_data.h264':
  Duration: N/A, bitrate: N/A
    Stream #0:0: Video: h264 (Main), yuvj420p(pc, bt709, progressive), 1280x720, 25 fps, 25 tbr, 1200k tbn, 50 tbc


  


  the file is being played on vlc, however the video is played like it is on fast forward (every 2 seconds of the video should be about 1 second)

  


  The video should run at 15fps (not sure about that because of the mentioned avi file)

  


  here is ffprobe output of working avi file that contain the video stream :

  


  Input #0, avi, from 't.avi':
  Duration: 00:03:29.00, start: 0.000000, bitrate: 1116 kb/s
    Stream #0:0: Video: h264 (Main) (H264 / 0x34363248), yuvj420p(pc, bt709, progressive), 1280x720, 849 kb/s, 30 fps, 15 tbr, 30 tbn, 60 tbc


  


  I tried this command ffmpeg -i frame_data.h264 -filter:v fps=15 test.h264 but the video is still playing like its on fast forward

  


  vlc data before changing fps to 15

  


  


  


  vlc data after changing fps to 15

  


  


  


  frames info (raw)

  


  [FRAME]
media_type=video
stream_index=0
key_frame=1
pkt_pts=N/A
pkt_pts_time=N/A
-> pkt_dts=N/A
-> pkt_dts_time=N/A
best_effort_timestamp=N/A
best_effort_timestamp_time=N/A
-> pkt_duration=48000
-> pkt_duration_time=0.040000
pkt_pos=1476573
pkt_size=57677
width=1280
height=720
pix_fmt=yuvj420p
sample_aspect_ratio=N/A
pict_type=I
coded_picture_number=189
display_picture_number=0
interlaced_frame=0
top_field_first=0
repeat_pict=0
color_range=pc
color_space=bt709
color_primaries=bt709
color_transfer=bt709
chroma_location=left
[/FRAME]
[FRAME]
media_type=video
stream_index=0
key_frame=0
pkt_pts=N/A
pkt_pts_time=N/A
-> pkt_dts=N/A
-> pkt_dts_time=N/A
best_effort_timestamp=N/A
best_effort_timestamp_time=N/A
-> pkt_duration=48000
-> pkt_duration_time=0.040000
pkt_pos=1534250
pkt_size=3928
width=1280
height=720
pix_fmt=yuvj420p
sample_aspect_ratio=N/A
pict_type=P
coded_picture_number=190
display_picture_number=0
interlaced_frame=0
top_field_first=0
repeat_pict=0
color_range=pc
color_space=bt709
color_primaries=bt709
color_transfer=bt709
chroma_location=left
[/FRAME]


  


  frame info from working (processed) avi

  


  [FRAME]
media_type=video
stream_index=0
key_frame=0
pkt_pts=N/A
pkt_pts_time=N/A
-> pkt_dts=500
-> pkt_dts_time=16.666667
best_effort_timestamp=500
best_effort_timestamp_time=16.666667
-> pkt_duration=1
-> pkt_duration_time=0.033333
pkt_pos=1772182
pkt_size=3070
width=1280
height=720
pix_fmt=yuvj420p
sample_aspect_ratio=N/A
pict_type=P
coded_picture_number=191
display_picture_number=0
interlaced_frame=0
top_field_first=0
repeat_pict=0
color_range=pc
color_space=bt709
color_primaries=bt709
color_transfer=bt709
chroma_location=left
[/FRAME]


  


  pkt_pts and pkt_dts are missing in the raw data, maybe that is the reason the video plays on fast forward ? in the working (processed) avi pkt_dts, pkt_dts_time, pkt_duration_time are not missing.
pkt_duration_time is always 0.033333
pkt_dts always jumps by 2 (there is no odd pkt_dts)

  


  Audio processing

  


  I have raw pcm audio of the video :

  


  here is an output of ffplay -f s16le -ar 16k -ac 1 frame_data2.h264 on the raw data

  


  

  


  The raw audio does not playing well using this command.

  


  I guessed the parameters (incorrectly ?) from working avi file that contains the pcm data :

  


  Stream #0:1: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, 1 channels, s16, 256 kb/s


  


  here is frame info from working (processed) avi file

  


  [FRAME]
media_type=audio
stream_index=1
key_frame=1
pkt_pts=4320
pkt_pts_time=0.270000
pkt_dts=4320
pkt_dts_time=0.270000
best_effort_timestamp=4320
best_effort_timestamp_time=0.270000
pkt_duration=480
pkt_duration_time=0.030000
pkt_pos=11670
pkt_size=960
sample_fmt=s16
nb_samples=480
channels=1
channel_layout=unknown
[/FRAME]


  


  I'm trying to understand how should I process the video and the audio so that they will play well (merge them myself with the right av processing to avi/mp4 file)

  


  I also find this extra data that was included for each frame :
I suspect the first column is a sequence number maybe related to dts somehow, second column is a timestamp (milliseconds ?) (maybe you can help me parse it)

  


  600 0xd96533 (audio)
601 0xd9e1dd (audio)
602 0xda4f52 (audio)
603 0xda5a63 (video)
604 0xdacc4b (audio)
605 0xdb39a3 (audio)
606 0xdb5ee9 (video)
607 0xdbb6d8 (audio)
608 0xdc23fe (audio)
609 0xdcb255 (audio)
610 0xdd0e69 (audio)
611 0xdd8b96 (audio)
612 0xdd67d0 (video)
613 0xddf8bd (audio)
614 0xde75fe (audio)
615 0xde6c28 (video)
616 0xdee328 (audio)
617 0xdf6012 (audio)
618 0xdfcd9d (audio)
619 0xe04a7d (audio)
620 0xe07523 (video)
621 0xe0b80c (audio)
622 0xe134db (audio)
623 0xe1798b (video)
624 0xe1a251 (audio)
625 0xe21f5c (audio)
626 0xe28ce1 (audio)
627 0xe27df7 (video)
628 0xe309a7 (audio)
629 0xe376fe (audio)
630 0xe3826e (video)
631 0xe3f3fd (audio)
632 0xe46154 (audio)
633 0xe486e9 (video)
634 0xe4de79 (audio)
635 0xe54bbe (audio)
636 0xe58b79 (video)
637 0xe5c8cb (audio)
638 0xe6361e (audio)
639 0xe6b35b (audio)
640 0xe68fb7 (video)
641 0xe72093 (audio)
642 0xe79db1 (audio)
643 0xe7942f (video)
644 0xe80b09 (audio)
645 0xe887ed (audio)
646 0xe8f546 (audio)
647 0xe97256 (audio)
648 0xe99d2c (video)
649 0xe9dfbd (audio)
650 0xea5ca8 (audio)


  


  Thanks.

  


• 7 Best Marketing Attribution Software in 2024

  22 février 2024, par Erin

  It can be hard to accurately track the impact of your marketing efforts across marketing channels and campaigns. That’s where marketing attribution software comes in. 

  It goes beyond basic web analytics solutions that just look at the final click. Instead, it shows how different channels, content, and ads are performing at every step of the buyer’s journey, which gives a more accurate picture than just focusing on the last click.

  In this guide, we’ll cover the basics of marketing attribution, list the top marketing attribution software and explain how the issue of privacy is transforming the web analytics industry.

  What is marketing attribution ?

  Marketing attribution is the process of assigning credit to each touchpoint in a buyer’s journey that leads to a desired action (such as a conversion or sale) in order to understand the effectiveness of various marketing channels and campaigns in influencing the customer’s decision-making process.

  Marketers use software tools like website analytics to to track and analyse customer interactions across different touchpoints, allowing them to attribute conversions or sales to specific marketing efforts and optimise their strategies and budgets accordingly.

  Why is marketing attribution so important ?

  If you don’t track your campaigns correctly, it’s easy to spend thousands (or even millions) in an ineffective way. A 2022 survey by Australian marketing agency Next&Co revealed their clients wasted AU$5.46 billion in ineffective ad spend.

  

  That’s 41% of all the ad spend tracked by Next&Co in 2022. A wasted marketing spend percentage this high isn’t exactly a recipe for a high marketing return on investment (ROI). And yet, it’s the average.

  Why is that ? 

  Most companies don’t actively track the results of their marketing campaigns actively enough.

  By improving your marketing attribution, you can determine which channels, ads, and campaigns work and which don’t. Then, you can move the budget from ineffective channels to effective ones.

  Even if you can only identify half of your wastage, this could be 20% or more of your total spend. Just imagine what your bottom line would look like if your marketing budget were 20% more effective.

  That’s the power that marketing attribution, when done right, brings to the table. It’s the road to a higher marketing ROI.

  Common marketing attribution models and how they’re different 

  The default model for attributing completed goals in most analytics tools is either the last interaction or the last non-direct interaction.

  However, some multi-touch models can help you get a more holistic view of the impact of your marketing efforts.

  

  • Last interaction model : attributes the conversion to the final interaction or referring source (campaign or ad).
  • Last non-direct interaction model : attributes the conversion to the final touchpoint that was not a direct visit to your website. (For example, if a search ad took them to a product page, the user bookmarked it and returned directly the next day to finish the purchase. The credit would go to the search ad as it’s the last non-direct touchpoint.)
  • First interaction model : attributes the conversion to the first referring event alone.
  • Linear model : gives equal value to every touchpoint throughout the customer journey. 
  • Time decay model : gives more value to touchpoints the closer they were to the actual sale.
  • Position-based model : gives more value to the first and last touchpoints — often 40% each, while splitting 20% among the rest.

  You can read our guide dedicated to marketing attribution models for more details on these models.

  Types of marketing attribution software and the impact of privacy regulations

  Until recently, digital advertising was the “scientific” advertisers’ utopia. Everything could be measured, with cookies from giants like Google and Facebook stalking every user across the web.

  But with the advent of regulations like GDPR and the CCPA, you can no longer blindly trust Google Analytics or the Meta Pixel without consequences.

  Multi-channel attribution tools with third-party cookies and GDPR

  Google, Meta, and other companies used to track and combine user data from their own platforms and websites across the web that installed their tags. These third-party cookies have long been under fire and have caused several GDPR fines.

  

  The alternative : analytics platforms with first-party cookies

  In a post-GDPR digital marketing landscape, a compliant-by-default web analytics platform like Matomo is a more reliable and accurate alternative.

  Plus, with a platform like Matomo, you don’t need to rely on data from digital advertising platforms like Facebook Ads and Google Ads. You can accurately track referral sources using our campaign tracking parameters.

  7 best marketing attribution software in 2024

  Below is the list of our favourite marketing attribution tools in 2024. If you find and use one that suits your needs correctly, you can quickly boost your marketing performance.

  1. Matomo — Accurate and easiest to set up for marketing attribution

  Matomo is a privacy-friendly web analytics suite that empowers you to accurately attribute marketing efforts and gain valuable insights while prioritising user privacy and compliance.

  Matomo integrates with e-commerce platforms like WooCommerce and Magenta. That makes it easy for B2C marketing teams to track the revenue impact of their campaigns.

  

  You can also compare a variety of attribution models against each other. B2B teams can use our API to integrate Matomo with their CRM.

  Pros :

  • Relies on first-party cookies for tracking, ensuring accurate data collection and attribution of user actions
  • Includes additional features like Heatmaps, Session Recordings, Form Analytics, A/B Testing, and more
  • Easy to set up and use
  • Features most common multi-touch attribution models

  Cons :

  • Limited to owned channels (website and e-commerce store) due to first-party cookies and data (but you can integrate other data sources through a CRM)

  Pricing

  The self-hosted version is free. The cloud hosted version starts at $19 per month and includes a 21-day free trial. No credit card requierd. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  2. WhatConverts — Great option for leads-based businesses with high ad spend

  WhatConverts is a marketing attribution tool with a focus on lead tracking. With most web analytics setups, it adds call and text tracking to the typical form-only tracking.

  

  Pros :

  • Reliable call and text tracking
  • Revenue attribution to specific leads (and, by extension, campaigns and ads)

  Cons :

  • Focused exclusively on leads — little utility for e-commerce companies 

  Pricing

  The cheapest plan starts at $30/month but does not include analytics integrations or form tracking. To access this and advanced flow tracking and attribution features, you need the Elite plan, which starts at $160/month.

  3. HubSpot Marketing Hub — Ideal CRM for larger B2B companies

  HubSpot is a marketing CRM with attribution features for tracking and analysis.

  

  The platform is very broad — encompassing CRM, email automation and other tools — which makes it challenging to use effectively. The price tag is also quite steep for smaller companies and marketing teams.

  Pros :

  • Concretely tracks revenue to multiple different touchpoints and marketing channels
  • Includes several different multi-touch attribution models
  • Allows offline conversion tracking

  Cons :

  • The price point is too high for smaller teams
  • Cam be difficult to set up effectively

  Pricing

  Since marketing attribution is only included in HubSpot Marketing Hub’s Professional and Enterprise plans, pricing starts at $800/month (paid annually). If you commit for a year but pay monthly, the price is $890/month for the professional plan. This goes up with additional add-ons and as your contacts increase as well. 

  4. ActiveCampaign — Good CRM option for small B2B companies

  ActiveCampaign is a CRM and marketing automation platform that can help you trace leads and revenue back to their source.

  

  Although it has a similar scope of features to HubSpot, it is more affordable and slightly easier to use for beginners.

  Pros :

  • Tracks sales revenue back to specific marketing touchpoints
  • Powerful marketing automation features

  Cons :

  • B2B companies may need to purchase two plans, one ActiveCampaign marketing and one CRM.

  Pricing

  Unlike HubSpot, ActiveCampaign offers a much more affordable plan, starting at $29/month billed annually (for up to 1,000 contacts). The marketing and sales CRM bundle starts at $93/month with up to five users.

  5. Salesforce Data Cloud for Marketing — Ideal CRM for enterprises

  Salesforce is a robust and feature-rich CRM that many enterprises rely on for their sales teams.

  

  That makes Salesforce’s marketing attribution platform a logical choice for existing Salesforce users.

  Pros :

  • Uses prospect and sales data from CRM to attribute revenue
  • Revenue prediction analytics
  • Lead scoring to help your sales team focus on high-value leads

  Cons :

  • Difficult to set up and use
  • Clunky and aged user interface
  • Relatively high price point

  Pricing

  The limited Marketing Cloud Account Engagement Growth plan starts at $1,250/month, billed annually. To access advanced cross-channel journeys, you need the Pro plan, which starts at $2,750 monthly.

  6. Terminus — Great for account-based marketing

  If your marketing team uses an account-based marketing (ABM) approach, Terminus might be the right option for you.

  

  It offers ABM tools like target account event tracking and revenue attribution tools for your marketing campaigns.

  Pros :

  • Advanced multi-channel revenue attribution tools with a wide range of reports
  • Track intent touchpoints back to target accounts
  • Reliable revenue predictions help you focus your marketing activities

  Cons :

  • Complex and difficult to set up, understand and use effectively
  • Lacks native integrations with many common advertising platforms and analytics tools

  Pricing

  Terminus offers no standard pricing plans. You must contact their sales team for a custom quote based on your needs.

  7. Adobe Analytics — An analytics for enterprises

  Adobe Analytics is part of the Adobe Experience Cloud, with plenty of big data analysis tools for enterprises. Although the platform is quite powerful, it is equally complex and difficult to use. The price point is also prohibitive for many smaller companies.

  

  Pros :

  • Very extensive reporting tools
  • Predictive analytics give you solid leading indicator for future campaign performance
  • Track multiple digital touchpoints across the entire customer journey

  Cons :

  • Like Google Analytics, Adobe Analytics aggregates your visitor data by default, making compliant “consent-free tracking” — tracking user actions without asking for consent — impossible according to GDPR. (See more differences in Matomo’s comparison against Adobe Analytics and Google Analytics.)
  • Prohibitively expensive for most smaller companies
  • Very steep learning curve for setting up and using it correctly

  Pricing

  Adobe Analytics uses usage-based pricing — which means they adjust the pricing based on the traffic volume to your website. Still, their lower price points aren’t exactly SMB-friendly — multiple sources put Adobe’s lowest starting price point at $2,000–2,500 per month.

  Get accurate marketing attribution with Matomo (without privacy concerns)

  Matomo allows you to do marketing attribution effectively and accurately without compromising your users’ privacy. By default, we only use first-party cookies and offer consent-free tracking – meaning no more annoying cookie consent banners (excluding in Germany and the UK).

  If you want to boost your marketing performance without disregarding your users’ privacy, get started with our 21-day free trial. No credit card required. It’s time to make more informed decisions about your marketing campaigns.

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