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NFT means to dawn consumer marketing on blockchain

Searched for “NFT meaning” in the past week? If not, you are missing a hype. But very likely you have and seen brand names jumping in for NFTs. They included NBA, Louis Vuitton, F1 Racing, Nike, and even Taco Bell.

NFT stands for the non-fungible token running on the blockchain. For a long time, your Clicademist has struggled to find an approachable link between blockchain and marketing. The sudden surge of NFT means it is time for marketers to take blockchain marketing seriously. Read on to know what, why and how.

NFT meaning

NFTs are non-fungible tokens. Fungible is an economic term for things of which any individual part is so alike others that they are mutually exchangeable. For example, on the blockchain, bitcoins are fungible, just like gold is fungible in the physical world. But the NFT can turn a piece of image.jpg on the Internet into a non-fungible asset, just like a golden palace is not easily exchangeable in the land of fairytales.

The magical touch is to stamp a digital property with the “smart contract” to mark its unchangeable ownership that everybody can trace.

With everything becoming more digital, so claims the Ethereum, NFTs provide a solution to add scarcity, uniqueness, and proofs of ownership to almost any assets.

NBA is selling “scarcity”. What is so rare?

Using NFT, NBA Top Shot becomes one of the first big brands to do content marketing on the blockchain. In October 2020, Dapper Labs launched the NBA Top Shot App with the tagline of “Own the best moments from NBA history”. A LeBron James moment of dunk NFT is priced at $213,000. The news says that by the end of February, trading of NBA Top Shot NFTs amounted up to $230 million, with the App still in the Beta version.

The arguments for NFTs are that they make digital properties rare, unique, and, therefore, valuable.

But wait a minute, how can NBA slam dunks be rare and scarce? There are tens of thousands of such moments. If those can be the cases of rarity, then how many rare and scarce moments can Walt Disney dig out of its Vault?

Rarity and scarcity may be true to luxury and exclusive brands. But for mass entertainment and sports brands, there must be something else that matters. That is the ownership mint by the smart contracts.

Smart contracts

Says Investopedia, “A smart contract is a self-executing contract with the terms of the agreement between buyer and seller being directly written into lines of code. The code and the agreements contained therein exist across a distributed, decentralized blockchain network. The code controls the execution, and transactions are trackable and irreversible”.

NFT trading and transactions are a chain of automatic executions of smart contract codes. The smart contracts confirm the transfers of ownership of assets from one to the next person.

Before NFTs, smart contracts were not easily accessible to consumers. One way to experience it was to buy and sell cryptocurrencies. Other forms of smart contracts were for B2B transactions in finance, energy, shipping and transportation industries.

The NFTs move smart contracts much closer to ordinary consumers. The Ethereum presents the cases of NFTs in the following areas. Most of these areas are related to consumer markets.

After the craze, marketing

NFTs at this moment are a craze. Spending $210,000+ to own some bytes of NBA_dunk.mp4 would never make sense. This bubble will burst to put one more creepy stigma on this crypto thing of blockchain.

But in the positive views, the true NFT meaning is to bring the technology of smart contract on the blockchain one step closer to ordinary consumers. This gives brands, especially those with items that need to be owned, unlimited rooms for marketing on the blockchain, which is to become the new Internet of Assets.

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Insights Learning

How smart, connected products are transforming Elon Musk net worth?

Driven by Tesla, Elon Musk net worth have been a super hot search query. Since a year ago on March 18 2020, Tesla share price has gone up from $71 by 10 folds, making him once the world’s richest man.

Tesla cars exemplify the Internet of Things technology. But how this piece of smart, connected product can generate such an unrivalled fortune? The marketing theorists of competitions and competitive advantages have given the answers.

Thus spoke Porter and Heppelmann

Michael Porter and James Heppelmann wrote in 2014 in Harvard Business Review that the technologies such as IoT have revolutionised old types of products composed solely of mechanical and electrical parts to become complex systems that combine hardware, sensors, data storage, microprocessors, software, and connectivity.

They used a farmer’s tractor đźšś in the original version of the infographic adapted below to show the revolution process. The “complex systems” reside in Stage 4.

Smart, connected electric cars using IoT technology drive the auto industry into new boundaries of competitions.

Replacing the tractor with an electric car, we can see that a smart, connected car forms a product system involving at least, but not limited to, manufactured deliverables, energy and maintenance services, plus data and connectivity capabilities.

But neither the Porter & Heppelmann’s tractor nor an electric car would stop at Stage 4. These complex product systems will cruise into Stage 5 – the “system of systems”.

A Tesla car in the near future will be a product system in a larger transportation system. This Transport System must also have a sustaining network of, for example, the GeoData, Energy Supply, and Communications systems.

The automobile industry today is in Stage 4. But stock buyers invest in the future. The rising Elon Musk net worth indicates investor votes of confidence in Stage 5 when Tesla would take an upper hand in competitions.

Change of heart

The two authors also suggest that smart, connected products not only change the competitions within industries. They also redefine industry boundaries in which the competitive dynamics are completely different.

Take another look at the infographic. In stages 1 to 4, the basis of competition shifts from discrete products to product systems.

In Stage 5, the systems of systems link an array of product systems together. Tesla will find itself competing in the broader driverless transportation industry.

Why would it have a competitive upper hand? That’s because automobiles will have a change of hearts to work their brains.

In the stages when auto companies competed on the product level, the internal combustion engines were the heart of cars. Carmakers spent tens of millions to design viable engines to be planted in different models and product lines.

Electric car engines are not that expensive to design and less difficult to build. In electric cars, batteries are the heart. More importantly, for self-driving electric cars in the era of the automated transportation system of systems, data processing and connectivity capabilities will be the brains.

The big tech companies like Tesla are more competent in building the hearts and brains of the new auto industry. They leave the traditional auto brands chasing their taillights from far behind.

American cars great again?

The smart, connected electric cars may rebuild the former glory of the American automobile industry because of the country’s power in the interlinked technology industry systems.

The American cars basked in the glories of the Ford Model T till the 1970s Oil Crisis. After that, global consumer preferences shifted to fuel efficiency. Japanese and German cars were the biggest winners of the shift, beating American peers badly.

But Elon Musk’s Tesla is leading the changes in the competitive landscape. It may eventually disrupt the world order of the auto industry because the smart, connected cars in the future run on the new battery hearts and the data-processing brains.

A new formation of American Big Techs, with Google and Apple in it, is joining the competition by becoming carmakers. They are set to make great American cars, knowing better how to programme the chips in them.

Elon Musk’s net worth today is because of the prospects of Tesla in the new global competitive landscape of tomorrow. It all started with cars becoming smart, connected. The magic of IoT.

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Insights Learning

Top secrets of digital marketing analytics

Marketing practitioners are in touch with digital analytics all the time. But there are a few secrets in digital marketing analytics that they need to know. Some of these may need the disclosure. Others may just be so common that they are left in blind spots.

Secret 1: Before marketers ask for it, analytics has already started

Analytics relies on data. Creation of data does not wait for marketers’ command to go ahead. Neither do processing and analysis of data. In the era of Big Data, data come from everywhere and all the time. They appear in both quantitative and qualitative forms, structured and unstructured, in big volume or in small batches. Analytics happens in real-time as data emerge, or more precisely when things happen.

For example, when one started to create a campaign plan the first question was always about what the situation was. The description of the situation was a result of some analytics that had taken place before the need to know arose. At this point, the marketer just opened the dashboard to look for some analytics to confirm the situation.

What markets need to do is to treat analytics as an on-going process and know where to hunt for the needed data. This requires them to be sensitive as well as informed. Remember, when Mike Bloomberg asks that everyone else bring data, he knows they should already have them.

Secret 2: The APIs are making all these to happen

When using digital analytics, not knowing about APIs is like opening a website without knowing the Internet. Whereas the analytics dashboards are like websites, the APIs are equivalent to the world-wide-web protocols to enable the exchanges of data and information.

API is the application programming interface, which is a group of computer codes to ask computers to exchange data with other computers. Clicademy has another reading to focus on this topic. Today all digital analytics tools use APIs. Scroll down their websites to read their documentation. Here is an example from Ahrefs about its API offerings.

Marketers do not need to deal with APIs directly, just like website users do not need to know what the www protocols are. However, marketers need to know how to discuss APIs and their capabilities with computer engineering teammates and those in partner companies. They need to have a say in what data are exchanged between the data owners and the fetchers.

Secret 3: What you see is mostly vanity

Pageviews, sessions durations, returning users, new users… how do these metrics matter? Sadly, among the several hundreds of measurements that marketing analytics tools show us, most of them are more for vanity than usefulness.

Not fearing to critically analyse our own data, your Clicademist acknowledges that we are in such a situation said above. We are yet to roll out our search engine marketing programmes, so the hits and views we get are the leaves without connections to the roots. What concerns our most is the sign-up rate, with very few site visitor’s journeys ending at the Goal Page.

Then what is not for vanity? The answer is to choose the correct KPI(s) which should correctly measure the current marketing performances of your organisation. Once set, the KPI metrics are the analytics that is useful. Others are just good to have but non-essential. For example, the current performance for Clicademy hinges on building site traffic and signing up members. The visitor-to-member conversion rate, measured by the visits to the Goal Page versus the total traffic is our focus.

Secret 4: Analytics are most useful when helping to create solutions to digital marketing problems

Good numbers and upgoing darts just tell a partial story. Digital analytics is more useful when it shows problems. Being able to see these problems and to make difficult choices to solve these problems make a good decision-maker.

Marketers constantly need to set objectives. After doing this many times enough, setting marketing objectives becomes the second nature. Digital analytics enables the so-called data-driven objectives. Marketing managers should build it into a habit to consider setting marketing objectives means to solve some problems. And they are able to see the problems because of analytics data.

It is a tough call when faced with the choice of to see problems or to see vanity from data analytics. So when next time your boss asked you to bring data, would you bring in problems or good news?

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Insights Learning

This tells differences between digital and traditional marketing

Let’s call the marketing before social media and Web 2.0 “traditional” marketing. Afterwards, there is this new digital marketing. The differences between the two are obvious, but hard to tell because of two reasons.

Hard to tell the differences

There may be no difference at all, primarily because of the strong inclusive and dependent relationships between the two. Digital marketing is a component of traditional marketing. It still uses the same systems, process, and strategies. Digital marketers use traditional marketing methods, such as segmentation, targeting, and positioning, to enable their practices. The new digital capabilities have not yet demonstrated their power to disrupt this profession.

Another factor complicates the differentiation. Marketing is becoming digital. The traditional practices are moving towards technology and digital platforms. Today a marketer inevitably thinks of digital marketing to kick off any campaign planning. Consumers feel the existence of brands more via digital channels than by physical connections. If digital marketing is taking over the whole marketing, what is the point to tell the differences?

The touchpoints

Trying to differentiate digital and traditional marketing by examining their mutual relationships leads to nowhere. But looking at their relationships with consumers instantly provides a solution. The solution lies in the consumer touchpoints that both digital and traditional marketing have to work on.

The consumer touchpoint is a cornerstone concept for understanding digital marketing. Scott Brinker, who produces the Chief Marketing Technologist Blog argues that touchpoints make this new marketing different.

In short, consumer touchpoints are where consumers and brands make contact with each other. Both sides could and would initiate the contacts, but businesses are generally more proactive.

There used to be mostly physical touchpoints. The traditional marketing mastered the skills to create and manage them. Stores and shops are prominent examples of such. McDonald’s restaurants counted customer footfalls as their most important performance indicators. But in the digital age, they have many more to number.

A picture is worth a thousand words

A search for “consumer touchpoints” online always lead to the featured image of above in various versions. This one is from Orderhive. It showcases the consumer touchpoints along the five-step buying process. Above the buying process bar in the centre of the picture are the touchpoints that digital marketing manages. Below the bar are the traditional yet still essential physical touchpoints.

This image shows the fundamental difference between digital and traditional marketing. That is the digital technology has created numerous new touchpoints for brands to engage with consumers.

Digital touchpoints are significant firstly they outnumber the physical ones. In this infographic by ratio of 13:8. The proportion in the reality can be even more skewed as marketers are upgrading traditional physical touchpoints such as direct mail and call centres into digital types.

The second significance of the increased number of touchpoints is the extended customer journey with brands. For example, Clicademy recently added an email newsletter service as an additional touchpoint with our users. Such extensions provide more opportunities for customer engagements and consumer experience enhancement, provided that marketers do the right things.

The third and most important significance of having more touchpoints is the possibilities for greater customer lifetime value (CLV), which is the revenues a customer may contribute during the period of relationships with brands. Digital touchpoints such as websites all aim at becoming the conversion points to transform prospect consumers into paying customers.

Busier marketers

This differentiation of marketing by consumer touchpoints relates to all marketers because there is simply more work to do. The new touchpoints are compelling reasons for marketers to make critical decisions on each of them. In addition, they need to constantly consider making more difficult choices of whether to keep or upgrade the traditional ones. Closures of high street shop fronts are not only due to dire financial ramifications but the responses to consumer’s choices of and preferences to digital touchpoints.

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Insights Learning

To clear confusions about marketing technology, use this guide

Marketing technology can be confusing because there is too much. A marketer with a Swiss-based sports federation recently told your Clicademist that she had to learn to use Figma, Miro, and Notion in the past few weeks, thanks to her new agency’s preferences. She confessed being an Office 365 user, she had not heard of any of these productivity tools weeks before.

The famous Marketing Technology Landscape infographics at its 2020 edition, has been struggling to be more informative than intimidating. All people can see is an agglomeration of logos to represent 8,000 plus technologies.

The problems of marketing technology

The rapidly growing multitude is one of the problems. Categorising the technology items as in the diagram below helps. But deep diving in even the smallest group of 601 Management solutions would not be practical.

Martech Category Growth 2019-2020
Marketing technology solutions 2020 categorised by chiefmartec.com. Click here for source.

The bigger problem lies in the interconnections between the technologies that every marketer deals with daily. There are at least three levels of connections. On the macro level are the technologies that come into our world. Next are the technologies as products and services provided by various companies and the competitors. On the operational level are the marketing technologies.

Your Clicademist uses the infographic below to demonstrate these relationships. The two moons stand for the marketing technologies in question.

There are three levels of interconnected relationships between technologies in marketing.

But imagine a star system with 8,000 and growing number of moons? No infographic can draw this massive scale of interconnections. We need a simpler solution to understand the relationships better.

Impacts of technology in marketing

Thankfully, we found the solution from the academians. George Day of the Wharton School of the University of Pennsylvania in a 2018 writing listed several technological forces that transform marketing. Three of those are particularly useful to guide people through the marketing technology maize.

We found a pattern of the marketing technology landscape by focusing on the impacts and leaving aside the issue of multitude. Let us examine these three impacts.

First, new ways of understanding and connecting with customers

Technology expanded marketers’ connections with consumers and clients. Social media alone have enabled such connectivity on a massive scale. The connectivity in turn has enabled data exchange. The data result in analytics to generate customer insights. The Clicademy data dashboard is such a prototype example.

Technology has also created more marketing touchpoints for businesses to engage with customers. These touchpoints provide connections for marketers to use some of those 8,000 technological solutions to engage customers with advertising and promotion, content and experience, and social relationships.

Second, advances in decision tools

Data and management categories of the marketing technology solutions embody this type of impacts. Marketing managers have always relied on data to make choices and solve problems. The differences today are the amount of data, the process of analysis, and the growing reliance on data.

Marketers also increasingly rely on technology to make and implement decisions. Human beings delegate this responsibility to computers. Automation is set to further disrupt the marketing industry in the days to come.

Third, new capabilities and competitors

This type of impacts is most exciting. A few years ago nobody would imagine the Apple Inc. to challenge BMW and Mercedes in the business of driverless cars. The creator of Amazon is compet IMG against the creator of some electric cars in an outer space race.

Technology brings new products and services to change companies’ business scopes as well as how people work. The cloud computing technology has brought about the three new tools which the Swiss sports federation manager has to work with. Those productivity tools are also commercial SaaS products.

Seeing these three impacts guides us to understand the myriad of technology in marketing. The first two have resulted in the marketing technology stacks used by the practitioners. These martech stacks are only to keep growing with the unstoppable third impact.

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Five things you must know about API in digital marketing

Over the past few years, the API has become a common digital marketing term. But marketers do not seem to take ownership of it, leaving it exclusively in the IT rooms. This is not right.

There are five things that every digital marketer today needs to know about APIs. So that they can take a proactive approach to command and use APIs in digital marketing.

First, what does API do?

We live in a world today with connected computers. These computers run applications, just like your phone runs the Apps. API stands for the “application programming interface”. It is a set of programming codes to tell the Apps to exchange data with each other in a controlled manner.

A common analogy is to compare APIs to restaurant service as this MuleSoft video does. Another example is that hotel marketplaces such as the Booking.com uses APIs to enable room providers (hotels and individual BandB owners) to share inventory and pricing in real-time.

Marketers can see the APIs as software that automatically collects data from other companies’ databases provided that the other companies also use APIs to allow such data accesses. With mutual consents, companies use APIs to let their computers talk to each other and exchange digital data.

Second, APIs share crucial data in business ecosystems

Why do companies want to and need to share data? It is because companies nowadays need to build business ecosystems in which partnerships are vital. Data owners need to give limited data access to clients, suppliers, and agents, to name a few. For social organisations and governments, automation in legitimate data sharing with the public is an obligation.

APIs are mainly business-to-business data exchange programmes. They are functionalities written into digital applications, therefore, has an indirect relationship with consumers. Consumers never download and install an API. Rather, they use applications with APIs running behind the scene.

Partly because APIs do not face consumers directly and partly because they are computer codes, marketers have not assumed responsibilities for them. This needs to change. Today advertising managers reselling Google, Facebook, Instagram, LinkedIn, MailChimp inventories must take a look at these platforms’ API development documentations to at least have an idea about the next point.

Third, what data are exchanged?

The short answer is all kinds of data. But two types are more relevant to marketing than others.

The first type is about the capabilities of the systems. For example, marketplace and advertising websites use APIs to manage transactions with advert agencies. Video hosting platforms allow developer APIs to detect the system and content specifications. YouTube provides API references and snippets for websites to embed videos and to track and control the playbacks.

YouTube embed and API reference
Video sharing sites like YouTube uses APIs for video embedding.

Another type is the performance data for analytics and consumer insights. Google and Bing analytics provides all developers with API accesses. Clicademy chooses to use Analytify to use the API access to create our site’s traffic dashboard with real-time Google Analytics data for registered members to view.

The scope of data access and exchange depends on the data owner’s need to build the business ecosystem. Data owners decide what and how much data to share. The data fetchers may have various level of bargaining power to request specific accesses.

Marketers must be aware that when it comes to accessing and sharing consumer data, ethics become a matter of concern.

Fourth, how should digital marketing staff take ownership of API?

Marketers do not have to be all capable. Coding APIs is an IT engineer’s job. Marketers should work with a team of software coders and involve themselves in deciding what data are needed and for what purposes.

It makes sense to advise marketers on how not to work with the IT developers. Please do not just ask them what are possible and available. This question is OK if you are asking them to help you choose between a Mac or Windows laptop. But when it comes to APIs, the answer will be a long list of technical possibilities, of which 90% are incomprehensible for laypersons. So your IT colleagues would respond to you with a more pointed question, “what do you need?” If you could not answer this question, a chicken-and-egg chase would start.

Marketers should command and use APIs as technological tools to assist decision making. They should ask for the API functionalities based on the need for insights and the decisions to make. If marketers are clear about their data needs, they are in the position to own the APIs created to serve those needs.

Fifth, how can you start to learn digital marketing API?

It would be difficult if you have never seen a digital marketing API in action. To use an API-enabled application would be the best way to learn the technology about its capabilities and results.

For this purpose, Clicademy recommends TAGS, which stands for a Twitter Archiving Google Sheet application created by Martin Hawksey, a learning technologist from Edinburg, Scotland.

TAGS uses Twitter API access to collect data from the social network and present the data in Google sheets. Digital marketing learners should try this application to get the first-hand experience of API-enabled social data collection and analysis.

Please register with Clicademy and subscribe our email newsletters to stay tuned for our future discussions on using TAGS as one of the first steps of learning digital analytics for marketing.

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Functions of digital analytics: sighting & solving problems

Digital marketing analytics solves problems. Even if all things go well, there is still a problem – how to do better? It is a constant battle for decision-makers to compete either against some rivals or themselves. Therefore Davenport and his co-authors argued 15 years ago that high-performing enterprises built their competitive strategies around data-driven insights and the resulting decisions.

Four functions

Digital analytics provide the functions for marketers to see problems and make decisions upon them. Specifically, the functions are of four types which are to report, explain, predict, and recommend.

These four functions follow a data analytics progression from describing the problems to the final step of recommending optimal solutions. In their 2019 book chapter, Prachi S. Deshpande, Subhash C. Sharma, and Sateesh K. Peddoju illustrated the information-to-optimisation progression. The figure below is an adaptation of their discussions.

Digital marketing analytics functions and types
Caption: Digital analytics and types (adapted from Predictive and Prescriptive Analytics in Big-data Era)

Digital analytics, according to the figure above, provides the sighting of the marketing problems in a sequence of hindsight, insight, and foresight. The ultimate purpose of the four functions is to optimise marketing value creation.

Corresponding to the four functions to report, explain, predict, and recommend are the well-known four types of digital analytics.

Descriptive analytics for reporting “what”

Descriptive analytics analyses data to tell what happened. It is generally the initial stage of data sighting. Since the data are about what already happened, the analysis creates hindsight.

The descriptive analytics mainly concentrated on “what” with the help of classification, clustering and segmentation of the data to discover patterns such as the central tendencies.

For such an example, Clicademy provides a data dashboard.

Diagnostic analytics for explaining “why”

The function of explanations using diagnostic analytics starts to create insights about why something happened. More complex analysis, often aided by computing power and algorithm, look for relationships between variables. This is the stage for the machine to learn about the patterns. However, the insights are still hindsight as of now.

Users of the diagnostic analytics need to be careful when taking the “why” as the causal explanation. It often requires controlled experiments to find out what caused what. More often, relationships between tested variables are correlations. Most A/B testings suggest correlations and associations between dependent and independent variables.

Predictive analytics for “so what”

Predictive analytics answers what is going to happen. Based on data patterns, analytics forecasts what will result from the predicted relationships between variables using regressions, simulations, and scenarios. This is the moment of “so what”.

Perhaps one of the most commonly predicted is how the current Covid-19 crisis will develop to affect every marketer in the world. Now the job is becoming more complex with the addition of a new deadly variable — the variants of the virus. It is the worst of the times for marketing, but one of the best times to see how predictive analytics works.

Prescriptive analytics for recommending “how”

Prescriptive analytics answers how to make the predictions to happen. This is the stage of decision-making. There should be a clear division of labour between algorithm and marketers. Computers are responsible for recommendations. Marketers make so-called data-driven decisions.

So this is the stage where marketers make the call. Analytics can point out the opportunities and even recommend how to take them. It is not that easy, though, to just follow the recommendations. It requires human judgement.

Conclusion

The digital analytics provides marketers with the functions to report, explain, and predict the problems and then recommend solutions. The time-reliant and increasingly automated sequences involve the four types of descriptive, diagnostic, predictive, and prescriptive analytics to inform marketers to make optimisation decisions.

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Insights Learning

Why and how digital marketing analytics are useful?

From pie charts to today’s dashboards everywhere, marketers cannot work without analytics. Marketing analytics have been in stay for decades. Digital analytics, however, has been the mainstream in recent years as everything goes online and digitalised. It has almost become a stand-alone craft.

Digital analytics gains the prominence largely due to the multitudes of the data and formats. In the good old days, a spreadsheet was sufficient to carry a company’s analytics. But in the digital era, a company’s analytics profile is complex. Website analytics alone using Google would have more than 200 metrics. What makes the situation more interesting is the speed of data creation and collection. Everything happens in real-time and a blink of eyes.

Despite the Four Vs of Big Data, digital analytics for marketing still falls in the realm of marketing analytics. This blog discusses the roles of digital analytics play in marketing to be useful for organisations. The roles are pretty straightforward.

In their famous Key Marketing Metrics book, Farris, Bendle, Pfeifer & Reibstein (2017) wrote,

Today marketers must understand their addressable markets quantitatively. They must measure new opportunities and the investment needed to realise them. Marketers must quantify the value of products, customers and distribution channels— all under various pricing and promotional scenarios. Increasingly, marketers are held accountable for the financial ramifications of their decisions. (p.2)

They summarised marketing metrics’ roles in organisations are to assess opportunities, performances, and accountability. But do not forget about risks.

Opportunities and risks

Digital analytics measures data collected internally and externally of organisations. Externally, the focus is mainly on consumers and competitions.

Consumer data enables businesses to understand consumer attitude and behaviours. Marketing decisions follow to engage and convert consumers into customers. The analytics work does not stop at monetising the insights. It continues to advise the efforts of customer relationship management.

Marketing analytics also help businesses manage risks. Social media monitoring is a common practice for firms to detect consumer sentiment. All social monitoring dashboards nowadays attempt to measure consumer sentiments to brands. A negative sentiment score would alert marketers to find issues and prevent them from becoming problems.

The ultimate purpose of identifying and measuring opportunities and risks is to set consequent marketing objectives, which are decisions to either take the opportunities or to walk around the risks.

Performances

Analytics measure how much results marketers have delivered. It is perhaps the biggest role that marketing analytics plays. Therefore the term KPI (key performance indicator) appears everywhere.

Monitoring performances relies mostly on internal data, for example, sales, revenue, and profit margin. Organisations tend to guard such data tightly unless they have to disclose, for example, the regular investor reports. Competitors crave for rival’s performance data. Marketing researchers and analyst value such data with the same level of interest.

Therefore it is unique for Clicademy to disclose its website performance data to assist the member’s learning of marketing analytics.

Performance data are significant by themselves. But they are even more meaningful when examined against objectives. This leads to the next role that analytics played.

Accountability

Effective marketers deliver performances that meet or exceed objectives. Marketing objectives must be aligned with businesses’ ultimate objective which is to be profitable. In the old days when marketing was a side-kick of the sales function, marketing constantly needed to justify its expenses.

The contemporary definition puts marketing management in the central and ubiquitous position of a firms’ value creation and exchange with customers and other stakeholders. This does not alleviate marketers’ accountability to the financial ramifications of their decisions. What has been changed is the scope of the marketing objectives. They are no longer only to the quantifiable contributions to the sales numbers. Meeting the qualitative value creation and exchanges objectives, for example, managing a firm’s social citizenship, can also justify marketers’ accountabilities.  

Down to the objectives

There is a common phrase which is “marketing objectives” to link up the three roles of digital analytics for marketing. A firm uses digital analytics to assess opportunities and risks, performances, and accountability of the marketing teams. They only make sense when there are meaningful and realistic objectives set and delivered.  

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Insights Learning

How do marketers stay relevant to marketing today

Marketing professionals need to adapt to the New Marketing driven by data and technology. Else, they would risk losing their relevance to this profession. These words are not dramatics.

Let us reflect on what happens when we hear or talk about marketing today. Before long the narratives would run into words such as the Big Data, artificial intelligence, the Internet of Things, marketing automation, etc. Marketing practitioners today not only have to talk and hear about these phrases constantly, but also deal and work with them on daily basis.

What’s your strength?

Obviously, these concepts do not traditionally belong to marketing. It is a challenge for marketers to take ownership of them. Marketing professionals’ strength has been in creativity, communications, and strategy. They are less comfortable working with computer codes and statistics. Likewise, marketing students tend to be more interested in Adobe Creative Cloud than SPSS, R, Python, and GitHub. Some of them still do not think they would ever need to touch them.

In a field with the ideal division of labour, statisticians and software engineers should take up the number crunching and coding jobs. But what if the labour now is about numbers and coding? Look again at those marketing buzzwords. They all require data and coding skills.

Contested field

For marketers, marketing has become a contested field. The increasing adoption of and reliance on data and software skills see jobs going to statisticians, data analysts, and software coders and engineers. It does not mean that creative and communication skillsets are not essential. However, marketing job seekers have seen recruitment ads noting analytics as essential skills and software literacy as preferred ones.

Marketing today has become technology-driven. To fuel its engine, data and computing have joined creativity, communications and strategy to be the core career assets. For the marketers who are strong in the latter set of expertise, their working relationships with the number and code persons are mutual supplementary in general. But peer-to-peer competition is looming.

In this wave of the New Marketing (We do not call it digital marketing and there will be a post to explain why), marketers should consider any or all of the three suggested approaches to handle the working relationships with colleagues who possess data and coding skills: to work with them, to work like them, and to lead them.

Relevant learning

To achieve any of these, one needs to learn how data analysts and software engineers work. Such learning will build up data analytics and software project development knowledge and skills. They can benefit multiple aspects of marketing. For example, data-driven agile marketing management, consumer understanding using data analytics, AI-assisted customer journey optimisation, new product development, automated customer relationship management, to name a few.

Building such knowledge requires a journey but is feasible within a manageable period of time. Clicademy in its next few series of posts will introduce concepts, tools and approaches that for our site visitors to learn data analytics and the New Marketing practices.

Clicademy links learning with reality. The site provides live traffic data to provide you with the first-hand analytic insights. You will need to register a membership to access the data analytics.