The KPIs to monitor for your campaigns

When we talk about KPIs, first of all, we’re talking about Big Data, which is the endless set of data that every company has at its disposal. To extract relevant information from Big Data, you’ll need to implement efficient tools, such as machine learning in order to collect, process, and analyze the data quickly, and make them intelligible through KPIs, which are metrics that measure performance of certain aspects of the business. There are many KPIs that you can examine that monitor different things, but once you carefully choose the most useful KPIs, they become a fundamental compass for every strategic choice.

A campaign is composed of different parts, all of which are fundamental for a successful project.

On the other hand, every campaign, even if it has a single “goal”, is actually made up of several aspects that combine different elements, different competencies that work together.

This means that there are many elements to take into account, in the phases of conception, realization, and then in the analysis and evaluation of the campaign.

For this reason, monitoring a campaign is not necessarily simple, even though it is fundamental since it is the only way to understand what went well, what needs to be modified, and what you should implement for the next campaign.

In this sense, data is a fundamental tool. Given the impact of digital transformation, data has become even more essential, provided that we know how to use it properly.

What is Big Data?

Every company has a large amount of data at its disposal, both internal and external data, which can provide information on many different aspects of the company.

This means being at the center of a veritable “storm” of information that, if not well managed and exploited, risks pushing towards incorrect decision making.

This is all the more true if we consider that digitization has increased the importance of data, but has also exponentially increased its volume.

That’s why we’ve been talking about Big Data for some time now, an expression that refers to the “large, hard-to-manage volumes of data – both structured and unstructured – that inundate businesses on a day-to-day basis.”

Obviously, quantity is only one of the aspects of Big Data. When we talk about Big Data, from the digital era onwards, we need to be more precise and recognize that there are actually 3 characteristics that define Big Data, as indicated by analyst Doug Laney in his now-famous definition of the 3 Vs:

• Volume: Refers to the huge amount of information that is generated and collected from various sources, such as business transactions, devices based on the Internet of Things (IoT), industrial equipment, but also in general from videos, social media, and activities performed by people online or on certain platforms;
• Velocity: Captures an interesting aspect of digital evolution, namely that with the increase in tools, devices, and the possibilities of using them at different stages, the speed with which data is generated has greatly increased and the time in which each company must collect it, analyze it, and then react accordingly, has been reduced.
• Variety: The third V ties in with what has been said above, namely that in just a few years, digital tools and their uses have multiplied. This means that a company’s data is available in many different formats, starting with structured and numeric data in traditional databases, passing through unstructured text documents, to email, video, audio, and financial transactions. Data, therefore, increasingly tend to take on different forms, different characteristics, and different levels of intelligibility. Companies must take these characteristics into account.

Although this trifecta is undoubtedly useful in delineating Big Data, it needs to be updated.

In fact, many scholars recognize other Vs related to Big Data that have emerged over the years and now deserve consideration.

One of these is Veracity: after all, having bad data could be linked to having no data at all. For this reason, it is fundamental that every piece of data that is collected and analyzed is also integral beyond any variation in format or source, since it is fundamental for strategic decision making.

The fifth V is Variability, which while it resembles the Variety we mentioned above, in reality it pertains to another aspect of Big Data. No type of information, regardless of its source or format, is an isolated object: each piece of data is always part of a larger context, which can change the meaning of the data and how it is interpreted. Companies must take this into account to actually understand and appreciate the significance of any data points.

The value of Big Data must be extracted

On closer inspection, given this reconstruction of the 5 Vs, to outline and identify the main characteristics of Big Data, one cannot ignore another V, which undoubtedly emerges from observing how the relationship with Big Data has changed in recent years.

In the recent period, all of the main economic players have become aware that Big Data is very important; some have even compared it to “oil”, i.e. a resource that must be extracted in some way in order to obtain its actual value.

In fact, in itself, a piece of data is nothing more than a codified representation of a phenomenon or an event that, therefore, has no intrinsic value; on the contrary, it acquires value if information is “extracted” from it, which is the output of an analysis process.

The sixth V suggests precisely this: every piece of data, in order to become a truly useful tool that can be used to make strategic choices, must be processed, refined, through Big Data Analytics methodologies in such a way as to acquire Value.

In order for this “transformation” to be possible, two things are necessary: the right tools and an effective system for interpreting data, which returns a clear and intelligible value.

Big Data needs Machine Learning

Big Data is a complex object, which in many ways is difficult to manage due to the amount and speed with which it changes and transforms.

This means that human labor must be complemented by tools that allow operators to usefully and effectively cope with all the data that is generated every day and needs to be processed.

Not surprisingly, many companies are implementing machine learning systems in-house, which is that “subset of artificial intelligence (AI) that focuses on building systems that learn—or improve performance—based on the data they consume.”

Machine learning, after all, is useful when it comes to having to manage large amounts of data, since it can not only collect and analyze it very quickly but also learn from it, identifying recurring patterns and indicating the best choices to make.

Among other things, machine learning is perfect for using Big Data to get creative. One such example is the Babelee platform, which allows you to cross-reference data and statistics in the company database relating to individual users in order to define the type of video to send and the timeframe for delivery.

Babelee is a digital platform that allows companies to easily and quickly create perfectly personalized videos from start to finish–with images, voice overs, or music) without having to involve the IT department or without the need to develop specialized skills in graphics and editing, but using video automation.

In this way, the processes of analysis, the creation of the video, the definition of the contents, and the delivery schedule take place in a fluid and automatic way, based on the initial data and from the data obtained from the subsequent consumption of the content.

You need KPIs to make the best use of Big Data

The second thing you need to make the most of the vast amount of data you have at your disposal are KPIs, which stands for Key Performance Indicators. KPIs are a series of quantifiable measures that companies can use to determine where they stand in terms of their operational and strategic goals.

As you can imagine, there are many different KPIs, depending on their respective performance criteria or priorities and, in general, they are important for directing marketing strategy and management, since they provide a sort of litmus test from which you can understand what choices to make and whether previous choices were successful or not.

To take full advantage of the use of KPIs, you’ll need to keep these two points in mind:

KPIs must be defined in such a way that factors beyond the company’s control do not interfere with their implementation, and above all, they must be measured over a specific time frame, with checkpoints at defined deadlines.

Also, KPIs and specific campaign objectives are two different things. Therefore, you can choose different KPIs to measure different things or at least different aspects of the same overall objective.

Which KPIs?

We can now move on to list the main KPIs that you can use for monitoring a campaign.

The most well known KPI is REVENUE, and it is basically used to determine if the campaign has had a positive impact on sales.

Having had an appreciable increase in sales means that the consumer has actually gone through the entire funnel, arriving at the final conversion stage, the one where he actually buys.

If the campaign is conversion-oriented, this is an important KPI to keep in mind, even though it may not necessarily indicate a successful campaign on its own.

The second KPI that you can use to determine if this increase in revenue has been achieved in an economically sustainable way is ROI.

ROI or Return Of Investment is used to establish the profitability of a strategy or a specific marketing operation.

ROI is one of the most important KPIs to take into consideration in order to effectively understand the cost required to obtain a certain result and whether it was worthwhile to reach it in that particular way.

To understand what this KPI actually says, there are two alternative approaches: the first is what is called strategic ROI, which makes an assessment of marketing operations as a whole; the second is attribution, which requires having a strategic and specific view of each marketing campaign, so as to understand how each one affects revenue.

The results are different: the first allows for an overall view, while the second is more segmented.

KPIs and consumers

KPIs also allow you to understand what kind of relationship the company is developing with its audience, i.e. how well the company is able to penetrate the target audience.

In this sense, an important KPI is the Customer Acquisition Cost, which indicates the cost of converting a customer, and is equivalent to the difference between the total costs of sales and marketing and the number of new customers in a quarter.

Another similar KPI, which capture a slightly different aspect, is the Conversion Rate, which is “a performance indicator used to evaluate the effectiveness of direct marketing campaigns” and which relates the actions performed by the user at different times and stages of the direct marketing process.

The interesting thing about the Conversion Rate is that it is an “elastic” KPI, since it can be remodeled according to the different campaign objectives and the context in which it is inserted. For example, in the context of digital marketing, the Conversion Rate represents the ratio between the number of conversions made and the number of accesses to the site in a certain period of time.

Remaining in the digital marketing field, many other KPIs allow to deepen the aspect of conversion and especially the relationship between the reactions obtained and the cost of each one: here then are fundamental to monitor the CPC (Cost Per Click), the CPV (Cost Per View), the CPC (Cost Per Conversion) and the CPA (Cost Per Acquisition).

All of these, together, provide very interesting indications regarding the sustainability of one’s strategy and can guide future choices towards greater economic efficiency.

Finally, still in the context of the company-customer relationship, there is a very interesting KPI to monitor, even if it may appear a bit nebulous: it is the Net Promoter Score, which is used to understand what is the perceived value of the company by consumers, asking them if they would recommend it to other people.

Obviously it’s a rather slippery KPI, but it undoubtedly allows you to get a first impression about how your brand is seen in the market, without forgetting that word of mouth is still one of the most important marketing tools. In general, when a person decides to become an ambassador, it means that he or she recognizes a value that goes beyond the quality of the product or service and that relates to the principles followed by the company or to the unique customer experience that it provides.