Digital
analytics & research

Digital marketing analytics is a system of measuring, collecting, analysing, interpreting and presenting information about website visitors. Monitoring the attendance of websites, determining their audiences and their behaviour are all vital for decision making in web development. Web analytics allows not only to improve websites, but also to optimise the budget for online promotion.

DIGITAL MARKETING ANALYTICS: PROMOTING BUSINESS ONLINE

Websites are the primary means of interacting with users online and converting them into actual buyers. To develop and implement a comprehensive promotion strategy for a commercial online project one must consider digital analytics.

Digital marketing analytics measures and processes quantitative and qualitative indicators of the enterprise. It allows us to improve communication with both current and future customers and implement both marketing and product solutions.

First of all, the analyst needs to determine the financial goals set for the project, the expected results, and the methods of their evaluation. According to Google, the most common business goals are:

• gathering information about users for the sales department (determining the target audience);
• sales of goods and services (e-commerce, see our article on core metrics for online stores);
• helping users find necessary information (e.g., support services);
• establishing communication, maintaining and increasing frequency of visits (e.g., web magazines and publishers);
• spreading information and increasing loyalty (brand awareness).

Decide on business goals, conversion efficiency, and online advertising campaigns based on:

• how to increase the ROI from advertising campaigns;
• how to increase the conversion rate on the website by improving its usability.

Conversion optimization is a set of measures taken based on digital analytics data, applied to the marketing campaign and related to interaction with users.

By the way, not only core metrics should be tracked and analyzed – measuring micro conversions is a way to optimize for a much wider audience since the average macro conversions conversion rate is 1-2%.

Analyze the current level of conversion

Goal: to find out to what extent the goals fulfilled. It is necessary to ensure that goals selection in statistical systems carried out correctly, there is no unnecessary information, and the commercial function of the website fully reflected.

Result: the formation of the current sales funnel along with the entire resource traffic and the necessary channels.

Transaction sequence

Analyze the whole purchase procedure

1. Goal: to study the behavior of potential customers at all shopping stages.
2. Result: identifying at what stage and why users abandon the website.

Analyze calls

1. The goal: to determine the quality and number of calls on all channels. You need to configure call tracking, which allows you to associate incoming calls with a traffic source.
2. Result: you will know how much traffic is converted to calls and come up with recommendations based on sources and channels.

Analyze the target audience

Objective: to study the visitors of the website and highlight the main groups. You should compare actual visitors with the portrait of the perfect client and determine the region of traffic concerning business targeted locations. You can also identify possible traffic accruals by corresponding partner websites.

Result: identification of the most commercially viable segments of the audience.

Analyze traffic channels

1. Aim: to study the efficiency of each channel.
2. Result: determination of the most effective channels to convert traffic into leads.

The advertising channel consists of the means of interaction that allow conveying the advertising message to target customers (e.g., search engines, social networks).

Sources of traffic are specific services used in the advertising channels. For example, sources of traffic on the “search engines” channel are Google, Yandex, Bing, Yahoo, and others; sources of traffic on the SMM channel can be Facebook, LinkedIn profile and so on.

Analyze semantic core and advertising campaigns

1. The goal: to evaluate the efficiency of the semantic core and advertising campaigns on all channels separately.
2. The result: we identify efficient and useless clusters of requests and advertising campaigns.

Сalculate ROI

Goal: to evaluate the efficiency of all advertising campaigns based on the return of investment.

The ROI indicator is the ratio of profit minus ad costs to the amount of ad investment. Analysis of the data related to the calculation of ROI almost always requires additional information:

• Customer Lifetime Value (CLV) — the amount of money received from one customer over the entire period of their relationship with the company;
• the share of margin in the end price of the product;
• the average amount of transactions made (if there is no electronic trade data);
• conversion rate (purchases made).

Calculate ROI out of consideration for CLV.

The result of the stage: actual information about the ROI of each advertising channel.

Analyze competition by channels

Goal: to find out on which advertising channels you are more/less effective than competitors. Use the “Comparison” report in Google Analytics — it can be found in the menu:

The report window looks like this:

You can see the difference between your and your competitors’ traffic channels, as well as the difference in loyalty indicators once the industry and the region of the resource are selected. Competitors can be sorted by daily traffic volume, a region of activity and industry.

The result: identification of inefficient channels, understanding of measures necessary to increase efficiency.

Evaluate the mobile adaptability of the website

1. Goal: to determine the mechanism of communication between users of mobile devices and the website.
2. Result: mobile adaptation or adaptation adjustment as a way to solve conversion problems.

Analyze bounce rates

1. Goal: to detect and examine pages of a website with a high bounce rate.
2. Result: prevention of traffic loss due to changes in such pages.

Organize data into a single unified report and prepare recommendations to select customer acquisition channels and optimize promotional activities.

1. Goal: to develop recommendations on how to improve advertising channels, marketing campaigns, and a website. You can also use ROI or the ratio of the complexity of all adjustments to the projected efficiency to prioritize problems in order of elimination.
2. Result: a viable plan on how to improve online advertising campaigns and predict the outcome (conversion and traffic).

Implement a systematic collection of data to control the effectiveness of investment and profit from online & offline advertising.

The use of digital analytics as a connecting and controlling element of advertising management allows for a sophisticated performance strategy development. Performance marketing should be thoroughly analyzed. The analytics indicates the specifics of returned investments and whether it is possible to improve the result.

Who needs analytics?

1. Marketers. It provides data on the cost-effectiveness of marketing channels and helps to optimize the budget reasonably.
2. Product managers. Analytics provides tools to calculate economic efficiency of the product, state hypotheses and justify the conclusions.
3. CEOs. Analytics provides end-to-end data assessment and full control over the funnel optimization and CPP reduction.
4. Strategists. Analytics reveals areas of business where you can start making more money.

What does an excellent digital analyst know?

Today when most businesses go online, digital analysts are in high demand. Even if companies do not earn online, they use the Internet as the main channel of communication with their target audience. Business needs specialists who can direct marketing, analyze data and give development recommendations.

Сompanies seek to hire professionals who can analyze vast volumes of data and draw conclusions. Every year the data amount in the world is increased by approximately 33%. In 2016, the Internet totaled 4.66 billion pages (without taking the deep web into account).

Today, unlike five years ago, in addition to Google Analytics and Yandex.Metrica, you need:

• to be able to work with Google Tag Manager;
• to understand A/B testing tools: Google Optimize, Optimizely;
• to understand data visualization tools: DataStudio, Tableau, Power BI;
• to understand competitor analysis systems: SimilarWeb, SEMrush;
• to understand social media monitoring systems;
• to step up to master or at least gain a deeper understanding of HTML and JavaScript;
• to consider studying SQL to work with BigQuery.

But even that knowledge is not enough today. It is necessary to understand when and why one should use a specific tool and how to do it effectively.

A competent digital analyst should be able to build a system of metrics, then evaluate, combine and interpret the obtained data correctly; understand user behavior, “feel” the product and look at it from a customer’s standpoint; form hypotheses, conduct research, and testing, draw the right conclusions, justify the results and collect reports based on the data received.

Online marketer and CEO should both be able to use the essential tools of digital analytics. Managers do not need to delve into technical aspects. It is enough to configure an interactive dashboard to display the daily report. The main thing is to understand how it all works. That’s why leaders of small businesses come to us to learn how to control the process and set tasks for online marketers correctly.

Scope of digital marketing analytics use

Web analytics helps in many aspects of website development and online promotion. Mainly:

1. Developing the functionality of a website based on visitors’ behavioral trends.
2. Evaluating the effectiveness of online advertising campaigns and search engine promotion.
3. Identifying weak spots in the structure, navigation, and content of a website.
4. Optimizing the line of products.

Gathering website attendance statistics allows us to understand:

• number of pages visited;
• keywords and phrases by which visitors find the website in search engines;
• geography of visitors;
• time visitors spend on individual pages;
• transitions between web pages;
• website audience (random, regular visitors, etc.);
• convenient website navigation.

Web analytics allows us to get answers to a significant number of questions regarding user behavior, such as:

1. How many visitors returned to the website and performed the target action after coming from a specific advertising channel?
2. What is the contribution of each traffic channel to sales over the reporting period? [multi-channel attribution]
3. Users from which regions and cities visit the website? How does their behavior differ?
4. How profitable is each source of traffic?
5. What is the value of each of the traffic channels?
6. How to optimize the costs of advertising campaigns and make budget development more effective?
7. What pages do users with mobile devices visit before leaving your website?
8. How do traffic and user behavior on your website differ from competitors?

The methods of analysis

• Traffic analysis: statistics, trends, absolute and relative indicators
• E-commerce data analysis: average purchase value, popular goods, revenue per traffic channel
• Usability analysis: clicks volume, user flow paths, page scrolling
• Behavior analysis: interaction with forms, micro, and macro conversions
• Benchmarking: the use of independent platforms to compare a website to general trends and competitors
• Cross-cutting analytics: tracking the full user flow path from an ad to the initial transaction (as well as repeated sales).

Five questions to consider in digital analytics

Consider several issues that will help you significantly improve the effectiveness of using analytical data in your company. It will help you look at the data from a different angle.

1. Can you trust your data?

Conducting an analytical audit is critical: this process questions the integrity and quality of your data and prompts you to find out what specific information you collect.

In a single analytical system, you should pay attention to many aspects. For example, ask yourself if your data sampled from Google Analytics.

That is a relatively simple question, but the answer to it is determined by how you manage your information. Maybe it has some value for you, and perhaps it does not. It may be necessary, but the accuracy is not so critical.

There are many ways to bypass the sampling problem in Google Analytics, but many other things threaten the integrity of your data. That’s why you should conduct a full-service check of Google Analytics regularly.

Ideally, this means that you need to analyze the data for each of your reports and, based on your intuition, determine whether it makes any sense. Is your bounce rate equal to 100% or 0%? It is likely that you have problems with duplicated tracking of page views or incorrect use of event tracking.

Sharp spikes often indicate implementation issues.

Usually, there is nothing complicated in solving these problems, but they are challenging to detect. A complete check of the analytical system is a non-standard process. Perform it at least once, and you will discover a lot of useful insights.

2. Is there something missing or do you have a complete picture?

Of course, you can trust your data to some extent, but that does not necessarily mean that it provides a complete picture. That applies to everything from the most common things to your Google Analytics account settings. For example, answer the following questions to set up the service:

• Is the default URL set correctly?
• Are your referral exclusions correct (for example, do you use PayPal to process payments)?
• Is extended link attribution enabled?
• Did you include reports on demographics and interests?
• Is Google Webmaster Tools correctly set up?
• AdWords integration:
  • Is it set up right?
  • Is PPC data displayed in Google Analytics?
  • Are clicks and sessions recorded correctly?

Another essential aspect that you should pay attention to campaign tagging. In Google Analytics tagging is performed using parameters in your URL. It usually looks like this:

//www.example.com/?utm_source=adsite&utm_campaign=adcampaign&utm_term=adkeyword

There are five UTM tags in Google Analytics:

• Medium
• Source
• Campaign
• Content
• Term

“Medium” and “source” parameters are mandatory, but you can also use a “campaign” tag to track individual marketing campaigns. “Content” tag helps distinguish several versions of content within a single campaign. Finally, there is the “term” parameter to determine the paid search queries that led to clicks.

Although many platforms, including AdWords and MailChimp, automatically add UTM tags to your URLs, some services do not. Thus, you can overlook the considerable part of your data that is absorbed by direct traffic or another channel.

To get a better idea of ​​your audience, you need to eliminate a lot of standard technical problems, for example:

• the lack of tracking code on some pages (which tracks and records visits);
• the lack of tracking code on “404” and “server 500” pages;
• the absence of manually implemented tags in personalized letters and newsletters;
• Violation of Google Privacy Policy by accidentally gathering personal information.

3. Is this data meaningful?

Unfortunately, companies often face the inability to rely on gathered data.

Even if your team is highly professional don’t hesitate to doubt and question the data to ensure it makes economic sense to use it.

4. Measuring and analyzing for weighty results

Once you’ve reached this stage, focus on the following aspects:

• Have you defined key events you want to track to gain comprehensive information about clients’ behavior?
• Have you determined conversion results/points, key metrics, and dashboards?
• Do you perform campaign optimization and segmentation?
• Have you developed a data-driven or behavioral client image to motivate and specify your actions?
• Are your data sources unified to ensure you can track most of the user flow path?
• Do you use behavioral targeting?
• Do you use predictive analytics?

The data is only useful if it aids you in making crucial business decisions.

Also remember that an overly conservative approach to data tracking can give the wrong idea about your clients’ behavior, so balance it out. You should focus on a selected group of metrics to save your team from frustration.

5. Was my analysis right?

There are two severe consequences to bad analysis:

1. It can lead to some wrong decisions. Beware: once the faulty conclusions are made (especially if they go well with some exciting ideas) it is challenging to take a step back and review the results to find out the mistake.
2. In the end, it shakes the belief in analyst (or a whole team of analysts) your organization has. Marketers make decisions based on data provided by analysts, so it also strikes back at them in a lot of ways.

You should lean towards common sense each time you analyze your reports and ask yourself if there is anything odd about those numbers. Keep in mind that it is better to double-check everything if numbers look suspiciously amazing.