What is Marketing Attribution? Definition and Types of Models

marketing attribution model
Do you have any concern about Attribution Modelling?

Marketing attribution has never been more impactful, yet complicated as it is today. Thanks to the influx of marketing channels and devices, layers of complexity are added to what was, a few years ago, a simple funnel.

Concurrently, data is easier to track, and there is a hype around tracking as much data as possible.

On one hand Companies with legacy data systems scramble to drill into marketing analytics without first renovating disjoint systems, On the other hand others overcomplicate attribution and spend endless resources to yield little actionable insight and lose on what to focus on in Marketing Attribution.

Despite the complexity, majority of marketers cannot say with certainty exactly how valuable each channel or touchpoint is during each customer’s purchase process.

 

Table of contents

  1. What is marketing attribution?
  2. Why attribution in marketing?
  3. Attribution in marketing: different models
  4. What is a touchpoint in marketing attribution?
  5. Goal and conversions
  6. Winning ingredients to a marketing attribution approach that works
  7. 5 Easy Steps to Build a Strategic Marketing Plan with Marketing Attribution
  8. Pitfalls and common mistakes
  9. 10 Common Myths about Attribution Modeling in 2023
  10. Wrapping it up

 

What is marketing attribution?

According to Wikipedia, in marketing attribution, or marketing attribution modelling is the identification of a set of user actions towards a goal, or a conversion, which we’ll refer to as touchpoints and then the assignment of a value to each of these touchpoints. The goal of marketing attribution is to get insights into what touchpoint or combination of touchpoints influences the individual towards a goal completion or conversion.

Marketing attribution is either missing from their analytics or overly complex. The result is the inability to optimize marketing budget. An effective attribution approach is what distinguishes an organization in the dark about its marketing spend from one that knows exactly how each channel is performing and allocates spend accordingly.

 

How digital marketing attribution modeling works?

You diversify your revenue streams to reduce risks, right? You have multiple channels and probably hundreds of campaigns running. And you need to understand their performance at scale.

So attribution software pulls the data from the channels you use and combine it into one customer journey, assigning credits to each interaction between your marketing and a customer. Learn how.

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Technically it happens with the use of IDs, cookies, clickstream data, etc. This data is usually siloed across the platforms, and you cannot analyze it holistically. So having it pulled up is a good thing anyway.

 

Why attribution in marketing?

Organizations which invest money into marketing activities, be it into paid media or own media, want to know exactly what working well and what is not working well. Knowing the performance of their individual activities helps them to stop wasting time and money on what does not work well and focus their attention on what works. In the history of marketing decisions were often done based on intuition and personal experience, which leads to a lot of money plainly wasted. 

McKinsey & Co. analysts … showed a typical range of 15% to 20% of marketing budgets could be reinvested in other activities or returned to the bottom line without losing marketing ROI … $200 billion of marketing spent annually could be put to better use

Source: “Smart Analytics can tap up to 20% of lost ROI

To put it short as to why attribution modelling is simple: To stop wasting money and outsmart your competition in decision making.

 

 

Attribution in marketing: different models

There are four types of marketing attributiopn models we are going to cover, single touchpoint models, multi-touchpoint rule-based models, algorithmic or data-driven models and econometric models. All of them provide different insights. In general, the goal when choosing the model is to model historical data in a way which is closest to mimicking reality. This helps to increase the probability of estimating future outcomes in the most economical way.

 

Single touchpoint marketing attribution

    • Last-touch or last-click
      The last-touch or last-click model gives all credit for a touchpoint to the last touchpoint or click a user has before a conversion event. This is by far the most used model as it comes as default with most advertising and analytics platforms. It leaves up all activity which happens in the upper funnel by nature of model it gives performance intent-driven channels such as paid search and organic search a heavy weighting. It often leads to wrong decisions (Adidas case).
    • First-touch or first-click
      This model gives all credit to the first touchpoint on the customer journey. The nature of this model gives credit to branding or upper funnel activities which occur at the beginning of customer journeys.

 

Multi-touchpoint rule-based attribution

    • Linear-touch model
      The linear touch model gives the same credit to each touchpoint in the conversion journey. It’s best to visualise this with an example. A customer journey has 5 touchpoints: 1. paid social, 2. display, 3. email, 4. display, 5. organic search. In this case, each of the channels gets 20% of the conversion attributed. Advertisers optimising on linear touch models often also include impressions and not just clicks into the model.
    • W-shape model
      The W-shape model attributes 40% of the conversion to the first touchpoint, 40% of the conversion to the last-touch and 20% to the touchpoints in the middle.

 

Algorithmic or data-driven modelling

Algorithmic or data-driven models allocate credit to each touchpoint based on probability theory. They simulate the impact of the removal of a touchpoint in customer journeys. Based on this the touchpoints get conversion credits attributed. There are two commonly used models in data-driven marketing attribution modelling, the Markov model and the Shapley value model.

 

Econometric models or media-mix modelling

For channels which do not have touch-points available from either digital or CRM channels such as TV, radio, billboards and print advertising, the impact is usually measured using a so-called top-down model. Here often linear regressions and ad-stock models are used. This is also best explained with an example: Acme corporation is in peak season and decides to run TV and radio advertisements.

The marketing team would like to know which channels and stations are the most effective. They decide to use an econometric model. From the digital and CRM side, they have the conversion journeys and from the offline advertising side, they have spot-plans which will tell them at what time of day on which channel how much money is spent. They spend $15’000 on a Wednesday night at 9.00 pm. Based on historical data they know the base-line of conversions and sessions on their website around this time, so they can attribute the uplift in sessions and the resulting conversions to TV and start understanding what time of day at what weekday is the most efficient.

 

What is a touchpoint in marketing attribution?

A touchpoint is an event a user or prospective customer towards the expected outcome (see Goals and conversions). Here are the most typical touch-points which are measured by marketing organisations:

 

Digital Touchpoints – measured in impressions and clicks

 

Offline touchpoints – measured using econometric models

    • Radio
    • TV
    • Billboards
    • Magazines

 

CRM touchpoints (only where applicable)

    • Tradeshows and Events
    • Sales meetings
    • Webinars

 

Customer journeys, also known as the path to conversion or conversion journeys, often involve multiple touchpoints in various sequences. The higher the product complexity or price, the higher the average of touchpoints is.

 

Goals and conversions

Measuring the efficiency of marketing and advertising requires a definition of goals towards one works to. In a sales environment, the goal is usually clear: Revenue. On the other side, in marketing, the goals are often not so clear. In marketing organisations often work with conversions goals and measure themselves against these goals. There are different stages of readiness in measuring outcomes.

 

Traffic

Here the goal is to get traffic to the website. The outcome is measured in clicks and sessions. We will not cover this in great depth in this article, as most organizations already understand that this is not an ideal form of measuring performance in a marketing department.

 

Cost per click or click-through rates (CPC/CTR)

As the title suggests here the measurement is a cost for a click and the click-through rate from someone seeing an advertisement or content to actually clicking on it.

The formula here is very simple:

CPC: cost / clicks
CTR: clicks / impressions

As for traffic, we will not cover CPC and CTR too much here in this article as clicks are a nice thing to have but they do not actually translate into business value unless you are a publisher selling advertising on your website.

 

Conversions

Conversions are what many organisations nowadays – with the exception of businesses which transact directly on the website as for example e-commerce and hospitality companies are doing – are optimising on. A conversion in most cases is a form fill. The metric which organisations on this stage of readiness are looking at improving is called cost per action (CPA), in some cases, it’s called cost per lead (CPL).

The formula here is very simple too:

CPA: cost / actions

Now, this is where it gets interesting: Organisations optimising their CPA know how much each action costs and can act on this information to bring the future CPA down. It, however, does not give any indication about the quality of the lead. In a very typical example:

Acme Corporation is looking at generating leads for their sales team and of course, the number of leads is not high enough. To help the sales team, the marketing team looks at which channels bring a scalable flow of leads and optimise towards more leads. Now the number of leads increases, but the sales team is still unhappy because many of the additional leads don’t convert into opportunities and subsequently into a business outcome. Now the marketing team spent a considerable amount of money and didn’t solve the problem. One further way of optimising is looking at their website and looking at the different conversion types they have: Online chat information submission, Lead form fill, General enquiry form. Now they look at adding additional dimensions to the data anlaysis: The use historical data to understand the probability of conversion type to opportunity conversion and they also use the average deal size across all deals and apply the following formula.

Average deal value * probability of conversion in percent

They do this per goal type and get what is called a weighted cost per acquisition or CPA. Optimising the budget on a CPA helps organisations to increase the quality and quantity of the desired outcomes.

 

Return on investment, ROI or ROAS

The most advanced and business outcome-focused way of measuring performance in marketing is a return on investment based.

The formula here is very simple:

Marketing spend / revenue

For companies which transact directly online, this way of measuring outcomes is the most popular as it is crystal clear. If the overall revenues outweigh the expenditures, the business is profitable. Businesses which don’t transact online often have a challenge similar to what was explained in 3) Conversions and the closest they can get with their optimisations are still based on guesstimates. Now if we jump back into our example of Acme Corporation:

To get to stage 4 their next step would be to link up their marketing data with their sales data. In order to do this they need to link up their advertising and analytics data with the CRM. The way they do so is by connecting both systems using unique identifiers to understand the touchpoints a user has online on the website to their CRM system. Now the setup is complete and marketing costs can be linked to sales revenue. Thanks to this the organisation can now measure the monetary value marketing generates and also optimise it. The executive management can now measure the cost of revenue across the organisation on a very granular level and allocate resources wherever needed.

 

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Winning ingredients to a marketing attribution approach that works

1. Select a model that fits the business model, and test it frequently

First click, last-click, U-shaped, time decay, Markov model, etc. are all types of models ranging in complexity that are used to attribute marketing value. However, none of them paints the exact picture, and every model, no matter how advanced, has its flaws. It is far more important to select a model that fits with the company’s business model as opposed to one that is simply the most advanced. To determine this fit, the organization needs to consider the nature of the customer journey.

Next, the selected model needs to be tested regularly, given the nature of the consumer journey inevitably varies with time. The perfect attribution scenario could no longer apply in a different season, where customers come through a seasonal campaign directly instead of multiple clicks through other digital channel.

 

2. Be dynamic with industry changes

There is nothing more detrimental to an organization’s marketing health than to rely on systems and models that are antiquated and require significant manual stitching. Legacy data systems need to be renovated to be able to connect with digital site data. Analytics should ideally be performed via data platforms instead of disjointedly across countless Excel documents.
Conversely, as new models are created, organizations need to evaluate their fit and adopt if they fit the business model more closely than existing models.

 

3. Maintain alignment between teams

Another non-negotiable for attribution success is that all parties need to agree on the goals of the attribution program, the key metrics involved, and the models being tested. The goal of attribution is to produce more revenue by spending more effectively, but without clear communication, some teams may fear that they’ll lose budget — and therefore status — and get territorial.

Attribution isn’t just a marketing issue. Installing more complex models will involve tech teams, and at the higher levels, the finance teams should be in on the goals of the program from the beginning. It’s generally acknowledged that over-crediting the bottom of the funnel (e.g., Google or Bing) means that funds will be unnecessarily tight for upstream channels. But if you can use attribution to show the value in those upstream channels, the finance folks might be persuaded to loosen the purse strings a little — but those folks need to be included in the attribution talks from the onset to understand the significance of the data.

 

4. Focus on LTV, not just conversion

Many companies simply track conversion and traffic as performance metrics. However, the fulcrum of an effective attribution program is the lifetime value, or LTV, of a customer.

Among the metrics your teams need to understand, the most important, a good attribution program, is the lifetime value (LTV) of a customer. Certain channels may not run a high conversion, but brings in high value customers such as the average LTV of a customer ends up higher than other channels. Furthermore, if you rely only on single-conversion events as the ultimate goal, upstream clicks get undervalued. The traffic coming in at the top of the funnel looks a whole lot more important if the end result is measured over time, not one single purchase.

 

5.Know when enough is enough

That perfect attribution scenario mentioned above?
You might as well accept the fact that you’re never going to get there — or, at least, not for the foreseeable future (and beware the tech provider that says otherwise). Every model, no matter how advanced, has its flaws. U-shaped, Game Theory, econometric, Time Decay, etc., are all nuanced and complex, and they give you more insights than simple last-click. But none of them paints an exact picture, so part of the secret of “mastering” attribution is knowing when good is good enough and when the pursuit of the ideal is just a dangerous rabbit hole.

 

5 Easy Steps to Build a Strategic Marketing Plan with Marketing Attribution

Building the annual marketing plan is never easy and with fast-moving new ad-formats and platforms, it’s becoming increasingly difficult. You need to take into account business goals and objectives to create a Strategic Marketing Plan with Marketing Attribution based on how to reach those.

It’s easy to either make the plan too complex and not actionable, or too rigid so it doesn’t allow for changes during the year. This depends on the industry and pace of change. How fast are channels, goals, and formats changing? These are factors that affect how much flexibility you should leave in the budget allocations and the marketing plan.

Building your marketing strategy with marketing attribution can make it easier. 

 

1. Business Objectives

 Sometimes, your marketing goals could feel like a random guess. That’s why they to be tied to wider business objectives and strategy. This involves having the right data to start with and communication between all departments.

 

Essentially, your marketing strategy should start from the main goals. Which are the goals and KPI’s the company wants to hit in the coming year? For example, the goal might be to double revenue or increase profits by 30%.

Less tangible goals could be for example:

  • To increase transparency in the spend and the marketing budget.
  • To gather more data for enabling learning and future optimizations

 

2. Marketing Priorities

After the business objectives are established, you have to prioritize. The marketing team has to decide and estimate where they can make a significant impact.

This involves communicating across teams and decision-makers and taking a closer look at your resources. It’s better to focus on priorities than spreading resources. In other words; it’s better to do a few things right than a lot of things poorly.

It’s important to be realistic about your capabilities. If it takes on too much there is a risk that no goals will be achieved as the efforts are spread too much. 

 

3. Marketing Goals

Your marketing goals are slightly different from business goals. These are tactical and quantifiable priorities that define what you will do to support the wider business objectives.

There are mostly four different categories of goal metrics: Impact, Output, Activity, and Readiness.

The impact is how much it affects the business goals.
The output is the result of actions.
Activity is the amount of activity
Readiness is how ready the marketing team is to perform.

This might be more tricky to define but once you do, you can move on to the building your marketing strategy.

 

4. Marketing Strategy

How will you reach prospective clients and how do you convert them into customers? Which channels are you going to use?

You probably already know that it’s not possible anymore to reach your goals using just one channel. So you’ll have to go multi-channel. But how do you know which ones?

To be able to formulate a good and realistic marketing strategy in-depth understanding of the customer journeys are needed. You’ll need to know which channels are the most cost-effective in different stages in the funnel.

You probably have some of the data to help your decisions already. First-click, last-click, and some multi-touch you can find in Google Analytics, Facebook Ad Manager, etc. But building a multitouch attribution, that takes into account all touch-points so you can see what works best, is not that easy.

That’s where Windsor.ai can come in to help you optimize your Strategic marketing plan with marketing attribution.
You can see which and across which channels customers reach you.

 

5. Key Actions

Both in terms of resources and marketing investment, you’ll need to find out the key actions.

  • What are the actions necessary to reach the goals?
  • How often will the plan be adjusted?

 

If you advertise mostly online and the marketing team is working fast as well, you can optimize it as you go along. On the other hand, if you, for example, run tv-ads you can only adjust and optimize it in slower cycles.

Most of our clients work on a weekly or bi-weekly optimization cycle.

Marketing ROI optimization

 

Pitfalls and common mistakes in marketing attribution

With so much data and options at hand organisations often drink from data firehoses and fail to look at the data in the right way which ultimately leads to inefficiencies.

Data firehose in marketing attribution

Organisations are increasingly drinking from a data firehose

Some of the biggest pitfalls in the world of marketing attribution modelling are:

 

Data silos

As mentioned in Conversions, businesses with data in multiple places often fail to evaluate their marketing expenditures properly. Some examples here are:

    • E-commerce companies seem to have a great return on investment on certain campaigns but the overall business results are quite bad as these campaigns actually attract customers which return the products, which ends up costing the company advertising costs, shipping fees and a product which cannot be sold again. Not knowing this in certain countries can have a critical impact on the business.
    • Businesses optimising on CPA instead of ROI: Bringing down the CPA and increasing the number of leads might not necessarily impact the business in a positive way at all as quantity and cost don’t tell us anything about quality. Only by connecting the data between the different silos using a unique identifier an organisation can understand the true cost per revenue.

 

Ad platform marketing attribution modelling

Most large publishers nowadays offer their own set of marketing attribution modelling software for optimisation. While they are definitely helpful for intra-channel optimisation, there are a few pitfalls to be aware of:

    • Cross-channel allocations
      Ad platforms don’t provide advice on how to reallocate budget across channels as they are only focussing on their own inventory. 
    • Double counting
      Ad platforms count conversions using their own pixel which leads to conversions being double-counted. A simple example here: A user sees an ad on paid social media and then goes onto a paid search platform. In this case, both platforms would take credit for the conversion.

 

Impressions vs clicks

Historically advertisers were able to track both impressions and click journeys across all channels. With certain publishers walled garden approach, it has become impossible to track impressions. So while some channels support impression tracking and others don’t it might look that channels are actually underperforming while they are clearly not. Here the only way, for now, is to revert back to clicks for all channels when looking at journeys as otherwise, it is impossible to have an apple to apple comparison between them.

 

10 Common Myths about Attribution Modeling in 2023

It is quite helpful to have expertise in handling attribution modeling as a successful marketer because it will help you identify the areas where you should spend and not spend your marketing budget.

However, sometimes, lack of knowledge becomes an issue and instead of revealing the truth, marketers start to make guesses regarding attribution modeling.

Marketing attribution if done correctly, can provide a complete insight to the marketers, and they can understand the behavior of their customers accurately.

But, if it’s not done the right way, then misconceptions and concerns will unearth. These concerns need to be resolved because attribution modeling cannot be blamed for the lack of results.

Here is a list of 10 common myths about attribution modeling that every marketer needs to understand and of course, leave behind.

 

1. You need a Degree in Rocket Science to understand Attribution Modelling

Typically, attribution modeling is analyzed and understood using the help of an attribution modeling software.

However, some marketing attribution modeling software’s are designed in such a way that they require a lot of knowledge to handle them efficiently. It makes things more complex because enterprises require extensive training to get the best value out of them.

But on the flipside, if you review the list of popular attribution models, they are not very complex to understand. Most models provide quick and easy insight into the performance of each channel, which really doesn’t require any extensive marketing analytics or number crunching science to understand.

Similarly, you can use multi-touch attribution modeling software like Windsor that is not only user-friendly and equipped with result-driven features but is also backed with data scientists to help you along with every step of the way.

 

2. Replacing Last-click with other Attribution Model might resolve issues 

Marketers are well aware of the most popular, last-click attribution model, which tracks the final touch point of a visitor before converting into a customer.

But, the real issue with this attribution model is that it cannot view the whole customer journey. It gives all credit to the last marketing channel before the conversion.

Due to this, marketers replace it with other static models like first-click, linear or time-decay so that the problem can be resolved.

But static models will only highlight specific areas of the customer journey towards conversion, not the whole process.

This is where you need data-driven attribution models that understand and evaluates the complete journey based on actual data and gives credit, where it actually deserves.

 

3. You need to have a Huge Marketing Budget

As most of the marketing attribution software’s are designed for the enterprises, which can afford any price tag. Some software costs well over 6 figures and even 7 figures in annual recurring expenses.

Though most of these software’s might be steeply-priced some of them are budget-friendly and reduces spend on the marketing budget. They give quick and visible ROI from marketing expenses.

For example, Windsor.ai is an affordable Marketing Attribution Software that can be easily implemented and delivers quicker Marketing ROI.

Check out these marketing attribution case studies to learn more about how Windsor helped organization’s save tons of marketing budget.

 

4. Attribution Modelling Is only helpful for Large Enterprises

Small and medium enterprises believe that attribution modeling can only be used by enterprises. They are only helpful for marketing channels with spending in excess of millions.

However, it’s only a misconception. If you are part of a small or medium enterprise, you can reap all the benefits of attribution modeling similar to large enterprises.

The key thing here is to discover marketing channels or campaigns that bring or doesn’t bring in results. And this objective is the same for each organization. The more targeted or result oriented your marketing investments, the better ROI you will get.

 

5. Using only Marketing Attribution Software is enough

Some enterprises believe that only having an attribution modeling software is what they need to do in order to fix the problem. But that’s not correct.

It is only the first step towards a successful marketing performance evaluation.  They help you in finding top performing marketing channels and successfully implementing them in your strategy. But it’s up to you to use them effectively for business growth.

 

6. Retargeting Last-Click Attribution might not be effective

Retargeting is undoubtedly an excellent technique to target already interested prospects.

Though Last Click Attribution Model might have its shortcomings, retargeting the last click marketing channel has its benefits. In some cases, it is the last customer touchpoint, before a conversion.

Targeting that channel can easily boost the sales of a business or whatever the marketing objective is. It also helps them to invest their marketing budget on a platform with more conversion possibilities.

 

7. Marketing Attribution only works for Online Marketing Channels

Since attribution software’s were web-based and focused entirely on online marketing channels, they didn’t account for offline or traditional marketing channels.

However, for a lot of enterprises, offline marketing proves to be a major success factor.

There are many businesses that are getting customers from marketing events, in-store activities, TV ads and so on.

Due to this, marketing attribution software accounts for offline marketing channels such as TV Ads Performance too. This helps in getting a much better picture of your marketing investments across online and offline marketing channels.

 

8. Marketing Attribution Is nothing more than Assumption

It is definitely a wrong belief that marketing attribution is totally guesswork because. It is designed specifically to monitor your marketing channels and how it accounts for business goals.

Sometimes, selecting a wrong model and less marketing expertise can make things worse. Marketers think it is because of the attribution model, which is nothing else but a clear misconception.

Data-driven attribution models use advanced machine learning and artificial intelligence algorithms to identify the true performance of each marketing channel.

 

9. Data can be Integrated with only limited Data Sources

Some marketers have concerns regarding data integration with attribution software. They think that it might be tough and sometimes, an impossible task to integrate all data. But that’s not the case.

Top Marketing attribution software like Windsor.ai understands these issues. It enables users to integrate any marketing data sources with its attribution platform.

It’s not only quite easy to integrate but also effective as well. The integrated data can easily be worked on and even pushed to 3rd party marketing dashboards.

 

10. The Brand Presence can’t be tracked In Long-term

Brand presence matters a lot to the business for long-term success because it has the potential of improving the sales volume.

Attribution modeling not only tracks the short term presence but also measures all factors that contribute towards the long-term presence of a brand. It just requires the right attribution model, software and experienced person to handle it successfully.

Attribution modeling help businesses understand marketing performance, credit the right marketing channel and create effective marketing plans. This powers their brand impact, engage customers, drive sales and improves marketing results.

 

Wrapping it up

You’ve integrated your data streams from your marketing channels. You have access to holistic raw data about the consumer interaction journey. But what attribution model are you going to use to base your decisions on the significance of each marketing channel?

There are a number of different options. You can go for “first-click wins”, where you place all the value on successful conversion into the first online interaction. You can go for “last-click wins”, where the value is placed on the last online interaction before conversion. You can do “even allocation”, and give equal credit to every step from the beginning to the end. Or many other approaches. These models are heuristic; they use a specific, straightforward approach in understanding the complex marketing cycle, which accelerates analysis at the expense of accuracy.

 

  1. Get all the data into one place before making any decision: With data silos in place, critical decisions are made on incomplete sets of data. If data is the oil of the future, you will need to look at your data pipelines now.
  2. If you are currently working with CPA metrics, start planning for the ROI age: Not only will it help you to get radical transparency, it will also save you a lot of money.
  3. Don’t rely on last-touch attribution modelling data: Marketing organisations which want to understand the impact of their work to the bottom line of the business definitely should look stay away from last-click attribution modelling.

 

FAQ

Marketing Attribution trends that will change digital marketing in 2023

Multi-touch Attribution Marketing

There is a big variety of marketing attribution models, but the trend is a multi-channel marketing attribution model. What does this mean?

When a marketer wants to track the right channel that brought higher conversions or sales, the main mistake can be a focus on the last touchpoint. If the customer saw your ad first on YouTube, then checked your website, then purchased your Instagram, it doesn’t mean that Instagram works better. It’s important to estimate the whole customer journey with the help of a multi-touch marketing attribution model.

 

Cross-Device Attribution

We are not only using different marketing channels at the same time but also various devices. According to the study, conducted by Google back in 2012, consumers use different devices to start their purchase. And as in 2022, we will have even more devices to use and marketing channels to apply, cross-device attribution is something marketers can’t avoid. 

Another study by Statcounter shows that desktop and mobile are switching roles. And, the emergence of new devices will increase this tendency. Maybe in the near future, we will get another device that will replace smartphones, for example. 

Instagram and other social media are improving and adding more features for shopping. Now, you can click on the Instagram picture and make a purchase. This will also reflect the way consumers use their devices. 

 

Nor sure where to start with marketing attribution?

 

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Access all your data from your favorite sources in one place.
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