How to define KPIs and improve Marketing processes

Much of Marketing is totally pragmatic. We actively look for a different way to view an issue, so that we can ask fresh questions, get different answers and create innovative solutions. Key Performance Indicators are classic example.

Here are nine thoughts on KPIs based on a variety of experiences across industries, processes and systems.

1 Part of the Big Picture

The purpose of KPI reporting is to support decision-making on critical issues.

The content is deliberately selective. It doesn’t aim to cover everything. Instead, it highlights key issues within a larger area. But what it does cover, it reports faithfully and without distorting the scale of the issue.

Reports highlight and summarise the essential issues accurately and concisely so that the Audience can understand the current situation. Their next step will be to ask questions and discover whether discussions are needed, whether decisions must be made.

2 Reporting as communication

When you stop and think about it, a KPI is a form of communication between a Reporter and their Audience. Ideally the reports will communicate meaning to the Audience without the presence of the Reporter.

For that communication to work successfully, the Reporter and Audience have to share a common understanding of:

  • Context – what the report is referring to
  • Content – what it means: why these units / this layout
  • Implication – which decisions can be taken using this information.

There’s simply no way that happens by accident.

In my experience, it’s a lot more productive to create, review, and refine those sketches on a white board before diving into the details.

Reporter and Audience must sit down together to define the essential business issues; identify what business decisions are linked with those issues; and sketch out how the relevant information should be communicated.

3 Form follows Function

The idea that report content must be self-contained and the display intuitive is important. But in the initial design stages, I think the graphical issues around Design of Information and Visual Communication are a distraction. I especially like Steve Jobs’ quote about the iPod, because I think it’s also at the heart of the whole KPI thing:

 “Design is not just what it looks like and feels like. Design is how it works.”

Steve Jobs on the iPod

If we take functionality as our starting point, a useful first question to discuss with the Audience is: “what function should the KPIs perform?”

Here are a few thoughts on different types of report.

Status A status report shows how something was at a specific point in time (“high tide was 1,2 m above normal sea level”), or how it is now (“body temperature is currently 36.8 Celsius”). To be meaningful, the display should also indicate whether the value is acceptable or not.

Performance Revolutions per Minute. Kilometres per hour. Website visitors per day. Purchases per week. Counts, volumes, values. These are often a variation on the status report.

Trend How an effect (by convention the y-axis) changes with variation in a cause (the x-axis). A classic example is revenues over time (months, quarters, years).

A trend report is often a status or performance report that includes recent history (“we got here via this path”). The danger of trend reports is the temptation for eye and brain to think it sees a pattern and use them as a predictive tool – which they most definitely are not.

Alarm Bell The function is to trigger action, so there has to be prior discussion and agreement between the Reporter and their Audience. First about the sensitivity of the trigger setting and second about the follow-up procedure.

After all, there’s a serious difference between: “ten minutes after the alarm went off, the team had put the fire out” and “the building is burning because no-one knows what to do when the alarm goes off”.

Crystal Ball Reports that suggest how things may evolve in the future (i.e. time-orientation). For example: “there’s enough reliable historical data available to indicate, via sound statistical calculation, how a situation might evolve in the near future within defined confidence limits”. And yes, the data analysis does have to be that pedantic to be valid.

Radar Screen What’s coming into view (i.e. spatial / conceptual orientation). Vitally useful in business and yet tricky to do because there are so many eventualities to cope with.

You might for instance, devote resources to following the science of new materials to identify opportunities for creating new products. Or you might put resources into tracking the evolution of customer needs. But it’s only by doing both that you can create a new product which satisfies customer needs.

Progress We might want to show how far we’ve come (“Year to Date”); or we might want to show how much remains to do (“quantity remaining”). To run a quantitative analysis, we need a data source of units that can easily be counted, such as time, resources, money or whatever. If quantative sources are missing, or to do a qualitative analysis, you might show milestones instead (“Stage 3 of the project is now complete; only Stage 4 is remaining”).

Flashing Lamp An exception report. “Hey! We spotted something. It looks like this and we evaluate this way. Let’s discuss whether we need to take action … etc.”

4 Applying these ideas to Marketing

It helps enormously if Marketers begin by clarifying who their Audiences are and what information they need.

Cars provide an easy-to-understand example

  • A car dashboard enables the Driver to operate the vehicle safely: the fuel tank is full, no warning lights are flashing, the seat belts are in use; etc.
  • When the vehicle goes in for maintenance, the Mechanic accesses an entirely different set of (historic) data, from a different system, for in-depth analysis – and gives the Driver recommendations (“it’s time to change the brake pads”).
  • The car navigation system enables the Driver to tell the Passenger how far it is to the destination, the expected time of arrival and whether to expect any disruptions en route.

In much the same way, Marketing departments need different types of report, according to the specific needs of the Audience. You get the idea.

5 Reporting by Marketing

In my experience, Marketing creates:

  • reports about itself, for its own use;
  • reports that communicate about Marketing to non-Marketers.

They’re very different in content and style.

Operation reports for Marketing Imagine for a moment Marketing as a ‘Black Box’. There are resources inputs (staff, budget, data) which are combined into processes (online, offline, etc.) to create outputs (events, leads, prospects).

The operation reports provide an overview of the health (effectiveness, efficiency) of that ‘Black Box’. They answer questions like. “are the operational systems and processes consuming the expected levels of resource and delivering the desired level of output?”.

Maintenance reports for Marketing These might be the reports from Team Leaders / Head of a function or system to the Marketing Director.

The top level is the summary of recommendations for action; below that is the analysis that explains the recommendation; below that, the details (once the method has been jointly agreed, the Marketing Director probably does not need to see these).

Navigation reports for Non-Marketers In parallel, there’s a set of reports that Marketing Directors want to share with Peers, other department heads and Stakeholders.

The purpose of these reports is to make sure that both left and right hand are working together to achieve business objectives. The format and content will depend on the audience: Sales, Finance, IT, HR, CEO.

6 A brief word on Data

It’s not always a good idea to begin with the data you’ve got, or what standard reports a system can spit out easily. Why? Because it limits your thinking.

Standard reports reflect an existing process. Using those reports the best you can do is optimise that process – which may actually be inefficient or unfit for purpose. A 1984 Rolls-Royce Corniche may be in tip-top condition – but the fuel consumption is unlikely to be better than 28 litres per 100 km (9 mpg UK).

Real improvement comes when you re-think how to achieve the objective and re-design the process. In practice, that often means collecting new data.

Defining what data you need to control processes (but don’t have yet) is itself a strategic objective. Rather than ignore it, you could put a hand-drawn sketch in the Report book labelled “feedback wanted” or “coming soon”, with a status update on the milestones toward delivery (data need defined / data capture started / report available).

7 Roll-up, Drill-down

Once you’ve outlined a report, you will probably need to think about data granularity. At what level of detail do you need to collect the data so that you can roll-up to totals, or drill-down to details?

The choices for data dimensions are almost limitless here:

  • Time: seconds / minutes / hours / days / weeks / months / quarters / years
  • Geography: ZIPcode / City / State / Country / Region / Continent
  • Etc.

And in addition to the generic ones, there are all your company-specific dimensions:

  • Customer segments
  • Product / Service categories
  • Internal organisation: sales regions, divisions, departments, etc.

As a side note: combining data from different systems can be very messy and resource intensive – but you probably knew that already.

8 Which subjects should KPIs cover?

Let’s go back to the opening comments. I suggested that: “KPI reports do not aim to cover everything. Instead, they highlight key issues within a large area”.

A useful question may be: “what criteria can we use to identify the key issues?”

I think that one set of considerations to use here is the ‘Black Box’ described above.

  • which activities / processes get the most Inputs (staff / budget / IT / etc.)
  • which activities / processes generate the most Outputs (volume / value)

In addition, I think a macro-scale version of the Navigation report may also be useful.

“How well is the company achieving its long-term objectives?”

To be able to communicate on that subject we need to know what the company objectives are and how the company defines the short- medium- and long-term. Direction, speed of progress and building new capabilities / infrastructures are thoughts that spring to mind here.

In this context, Marketing needs to communicate about things like:

  • staff: development & retention, successor planning, building in-house skills
  • systems: data collection, quality, integration, privacy by design
  • processes: online and offline, how to join them seamlessly, digitalisation & re-design
  • budgets: for ongoing operations / for investments in new capabilities, infrastructures

9 Looking to the future

One thing that can help Marketing increase effectiveness is to make a mental transition “from Project to Process”.

Many teams within Marketing tend to think of the year as a sequence of projects. For example: Online does a series of Lead Generation Campaigns; Events does a series of Trade Shows; Corporate Communication does a series of Articles; Product Management does a series of Brochures. Start a project, finish it; start the next one … Repeat.

Another way of looking at this is to say that each team manages a process that produces Campaigns / Events / Articles / Brochures / whatever. Each process combines a set of resources, skills, data, systems and budget in a specific manner to achieve a result.

So what would happen – bear with me, I’m thinking out loud, here – if we turn our Marketing professionals loose on those processes and challenge them to find new ways of combining resources?

Perhaps we could create a Trend chart showing “Total Resource” per “Project”. To begin with we might see large variation from project to project. Focussing on this aspect could lead to stabilisation. After a while, there might be optimisation. And if we allow people to re-define the process, ideally there will be a stepwise reduction in the amount of resource required per project.*

This brings us back to the beginning: the purpose of KPIs is to provide insights that we can act on. Meaningful KPIs enable us to monitor and re-design today’s systems and processes, so that we can achieve the desired objectives with greater efficiency and effectiveness tomorrow.

*Note: These ideas are neither original nor new. They come from the Quality Management approach used in manufacturing production. The improvement is the result of changing the process by experimentation. Please note that it’s impossible to get improvement simply by setting a target.  See: Deming “Out of the Crisis” chapter 11 Common and special causes of improvement.

Data driven marketing

Rational decisions based on facts and statistics are more likely to get you the business results you want – such as growth, profits and customer loyalty. That’s the promise implied by “data driven-marketing”. And it’s a whole lot better than intuitive decisions based on qualitative information, ‘gut feel’ or experience. Or is it?


Forrester reports that, in the USA, the companies that are best at data science …
• are twice as likely to be leaders of their segment
• have significantly higher revenue growth and profits
• and: are most likely to be in the size group 1.000 to 5.000 employees.

Now its tempting to read this an endorsement for data science. Also, to infer that data science is potentially the ‘Secret Sauce’ for improving business results among the Hidden Champions of the Mittelstand. There are two big ‘buts’.

First: Correlation is not the same as causation. Second, we need more information to determine what is cause and what is effect. Did those companies in fact become the best at Data Science because they spent twice as much budget on it than the others?

The goal of data driven marketing is to create clarity and enable action. Revealing patterns, trends, and associations, especially relating to human behaviour and interactions sounds like a great idea. But we can’t take data ownership for granted.

Sunand Menon notes that “many organisations assume that if they collect the data and house it in their systems, it must be their data”. But any processing of personal data in the EU immediately falls within the scope of GDPR. So it pays to evaluate data ownership early on, and if in any doubt at all, to get legal advice from a lawyer or Data Privacy expert before starting.


“It’s critical to treat customers and their data with respect.”


Where to begin?

How can marketers get started with data-driven marketing? Brad Brown suggests that managers first ask themselves “Where could data analytics deliver quantum leaps in business performance?” The next steps are to define a strategy for data analytics and implement it. While this may be a valid approach for large enterprises, it does not seem appropriate for the Mittelstand. This scenario describes a technique in search of a raison d’etre. In mid-size organisations its called “putting the cart before the horse”.

In a brief “how-to” article, Thomas Redman advocates these steps to data analysis:
• formulate a question and write it down
• collect the data
• draw pictures to understand the data
• ask the “so what?” question

The “so what?” evaluation tells us whether the result is interesting or important. Many analyses end at this point, says Redman, because there is no value beyond the “so what?”.
Given that Mittelstand Marketers can afford to waste neither time nor resources, it makes more sense to ask the “so what?” question before we even start collecting the data. That way we can focus on the questions that will deliver result that are both interesting and important.


Common data standards

Before we can analyse the data, we have to get hold of it. Data mining – identifying and using the data you already have – is a sensible place to start. And yet this is where the difficulties begin.

Companies often hold data in multiple systems. Systems that were originally designed to serve distinct business units, departments or organizational functions. These systems were often built without reference to each other. As a result, they frequently use inconsistent data definitions and structures – even for the simplest of attributes.

The international standard ISO-3166 for example, defines several ways to describe countries: Alpha-2, Alpha-3, UN M49, Name. (thus: Germany, DE, DEU, 276). To marry up systems that use different definitions, the structure must first be recognised and then translated into a common format before the data can be combined for analysis. In very old systems however, the programmers may not have used ISO codes for standard dimensions and characteristics, which creates further complications and additional work.




Silos make it hard to manage and analyse enterprise-wide data. This example is just the tip of the iceberg. Suffice to say, integrating data from a variety of silos is slow and resource intensive. Companies that have grown by acquisition will know this situation only too well. Rather than try to integrate two completely different systems, the usual decision is to keep one and close down the other.

There’s another factor at work here. The reality is that old systems reflect old business practices. And this has two important implications, both of which are uncomfortable. On the one hand, the way data is stored and processed today is not necessarily relevant for deciding the processes you need today or tomorrow. The reverse is also possible: there may well be types or categories of data that you need for an analysis, that simply aren’t available in the way you want it, because it has never been collected in that manner.

An example of this is the software vendor who sold a bundle of products using a single contract with a single price on the invoice and a single line entry in the CRM. It proved impossible to analyse accurately the market penetration, revenue attribution or competitive situation for each of the individual software products in the bundle. The information could not even be estimated by analysing customer technical support enquiries. The lack of information and insights at the desired level of detail hindered budget allocation, investment in product development and planning of marketing activities.


72% of companies say that managing multiple CRM systems across geographies/ technology silos is challenging


Next up: you may want or need to combine data from two different systems – only to find that they have been designed on a completely different view of the way the world works.

A classic example is the B2B Marketer who wants a “single view of the customer”. To achieve this, data from the CRM should be combined with data from the Online Marketing system. This is easier said than done. In the B2B world, CRM systems are designed around the fundamental unit of a customer organisation – each of which may have multiple contact persons. By contrast, the basic unit in an Online Marketing system is a contact person – and that contact person record can exist without belonging to a business.

Mapping contacts from the two systems against each other causes headaches whichever direction you try to solve it. The headache is that some data simply cannot be integrated – and is therefore unusable for analysis. Any loss of data in the analysis means a loss of accuracy in the evaluation.

“Rubbish in, rubbish out” has been a mantra of computing since the earliest days; the need for data quality acknowledged and understood. But once again reality gets in the way of the two key characteristics of data quality. Data completeness means that if you decide to add a characteristic to a database, you must add this piece of information throughout the entire database. Similarly, if you’re going to collect data, it has to be accurate – both at the time of collection and later on at the time of analysis.

As we know, the world is in a constant state of flux. Dun and Bradstreet – an organisation that provides credit rating services for business – invests huge amounts of effort in keeping its records of millions of global organisations up to date. The company knows only too well how fast the world is changing.


Each minute of an eight-hour working day:
• 211 business will move
• 429 business telephone numbers change
• 284 executive or business owners will change.
Dun & Bradstreet


Faced with large volumes of data and the rapid velocity of change, it’s clear that a one-time data analysis project is going to have a very limited half-life for supporting decision-making.


Accessibility in real time

When data analysis is repeated on a regular basis, data quality becomes even more important. The data collection, cleansing and integration steps have to be repeated efficiently and effectively.

To improve data quality Thomas Redman advocates establishing a process management cycle. The first step is to measure data quality; the second, to decide which approach to use to improve quality. Redman lists and comments on three choices:
1. Unmanaged – not recommended.
2. Find and fix – resource intensive.
3. Prevent errors at the source – the best option.


“Improving data quality requires a cultural shift within the organization.”


Preventing errors at the source implies a change in practice. Instead of analysis being implemented as an activity (whether manual or batch), it has to be re-designed to become an ongoing process. A more advanced line of thought is to re-design and implement business processes so that they automatically generate the data that is needed for analysis. Data as by-product of daily business, in fact. This transition from activity to process is a central and recurring aspect of digital transformation in marketing.


Data analysis

Data analysis describes the process of inspecting, cleaning, transforming, and modelling data to gain insights that support decision-making.

By establishing baselines, Marketers can identify patterns such as (say) seasonality. By distinguishing between noise and signal, medium-term trends can be accurately identified, enabling marketers to re-allocate resources more quickly in response to evolving markets.

Scott Neslin advocates analysing the sales recency curve to investigate whether or not to invest marketing budget in a customer. He acknowledges that the results can be ambiguous. The sensible approach, he says it to derive an action plan from the data, test it and measure the results.


“A lot of stories emerge from customer data.
The trick is figuring out which story to listen to.”


For Harald Fanderl, the greatest value of analysis comes from “pinpointing cause and effect and making predictions”. To improve customer journeys, Fanderl examines just the top three to five that contribute most to customers and the bottom line. “Narrow the focus to cut through the data clutter and prioritize,” he says.

What about sales managers – which metrics should they track? Scott Edinger prefers to measure the process rather than the outcome because managers have control over the process; whereas the outcome is determined by another variable which cannot be controlled (the customer).


“Managing the things you can control, will give you the best chance for success.”


The simplest analytics questions can be enormously powerful. Michael Schrage uses the Pareto principle to ask which 20% of customers generate 80% of the profits. And then he iterates this approach to identify the most profitable segments for future action.


“Learn which customers are profitable and which ones aren’t.
It makes it easier to see the opportunities.”


The goal, says Chris Briggs, is to: “make informed decisions and not let the numbers lead you astray.” Though this is far from easy. As Andrew O’Connell and Walter Frick observe, the numbers don’t lie but: “can be slippery, cryptic, and, at times, two-faced. Whether they represent findings about your customers, products, or employees, they can be maddeningly open to interpretation.”


Advanced analytics

A good analysis provides a marketer with reference data that have predictive power. These insights are more than just a one-off event; they are patterns that describe baselines, trends, relationships.

There are several types of pattern that regularly appear in both the natural and man-made world: standard distributions; time series; 80:20 Pareto relationships; power curves with longtail distributions; direct and indirect causal relationships. Each of these describe a different context for analysis.

The approach to finding these patterns will depend in part on the available resources. If huge amounts of data, of high quality (completeness and accuracy) are readily available from a small number of systems and require little effort to integrate, then machine learning may be a good option. Machine-learning software identifies patterns in data and uses them to make predictions. So the work sequence is to let the machines identify the patterns in the data; and then test the patterns for their predictive power.

But who exactly is going to do the analysis? And what do you do if your organisation doesn’t have the skills or tools in-house? “Small and medium-size businesses are often intimidated by the cost and complexity of handling large amounts of digital information,” says Phil Simon His solution: hire external data scientists via websites such as Kaggle [].


“Kaggle lets you easily put data scientists to work for you,
and renting is much less expensive than buying them.”


If on the other hand, the data is lacking in volume or quality, or if integration from disparate systems requires a lot of time and effort, then the best approach may be to begin by narrowing the scope of the project. Marketers do this by focussing on a clearly defined hypothesis before defining what data is necessary and which analysis will prove or disprove the hypothesis.


“In a world that’s flooded with data, there’s too much of it to make sense of.
You have to come to the data with an insight or hypothesis to test.”


At the very root of data driven marketing is the ability to ask powerful questions. Asking questions is a skill. It is possible to develop it and get better at it, with practice, over time.

One approach is to reverse-engineer the issue and identify the really powerful questions by starting with a clearly defined goal in mind:
• What decision do you want to make?
• What insights will enable that decision?
• What questions will generate those insights?
• What data do you need to answer those questions?

Managers who have internalised their knowledge of a subject and their experience of a field, know –seemingly intuitively – which questions need to be answered and whether it’s worth investing effort in rigorous data-driven analysis. Perhaps this is why Page 7 of the Forester report states: “48% of companies use intuition over data to guide their decisions”.


Human vs machine

So who makes the better decisions – the human or the machine? Andrews McAfee is one of several writes who has researched this area. In his view, “data-dominated firms are going to take market share, customers, and profits away from those who are still relying too heavily on their human experts”.

“When experts apply their judgment to the output of a data-driven algorithm, they generally do worse than the algorithm alone would,” he reports. “Things get a lot better when we flip this sequence around and have the expert provide input to the model.”

MAfee quotes from Ian Ayres book Super Crunchers: “Instead of having the statistics as a servant to expert choice, the expert becomes a servant of the statistical machine.” In other words, the expert’s job is to ensure that the process is: “quality data in, quality insights out”.


“The single biggest challenge any organization faces in a world awash in data is the time it takes to make a decision.”


Which brings us to the issue of what we actually do with the results. It may be a good idea to listen to Tom Davenport ‘s comment on decisions. In the final analysis, there’s not much point in investing time and effort in data-driven marketing, if your management team can’t or won’t act promptly on the insights.

There’s more to digitalisation of marketing than just online

Marketers in manufacturing say that their top two marketing objectives are (1):

  • presenting the quality of the product (or service) effectively;
  • and winning sales leads among prospects.

Now, online tools are great for achieving these objectives. At the last count (2) there were over 5.000 software products for marketing, in categories like Advertising & Promotion, Content & Experience, Social, Relationships, Commerce, Sales and Data Management.

And there are endless opportunities for combining them. So yes, both those objectives can be achieved via online techniques. Tick that box.

The bigger picture

But the fact remains: these are not the only tools in the Marketers box.

Offline communication continues to be vitally important for B2B marketing (3). Articles in the trade press are highly rated as information sources by buyers. Printed materials still have a place in pre-sales and post-sales communications.

Trade shows don’t suit every company. But organisations that do take part in trade shows invest heavily, typically devoting over 40% of their marketing budget to them.

Face to face communication – for the time being at least – continues to be the key element of B2B sales.

Why? Because it is essential for building the business relationship that leads to the sale.

Especially for sales that involve any of the following classic B2B characteristics:

  • technical complexity (expertise of the supplier)
  • company-specific solution (many questions to be answered)
  • high price tag (commitment to the supplier)
  • long-term implications (partnering with the right company?)
  • complex decision processes (impact on multiple departments)

I think the biggest hurdle to the digitalisation of marketing is in our heads. To the person with a hammer in their hand, there is a temptation to treat everything like a nail.

Questions that are prompted by technology, or that focus on technology are most definitely not the questions that help us address business issues.

  • “How do we create a strategy for digital marketing?” describes a lop-sided and incomplete view of the issue.
  • „What can we do with this shiny new tool?“ starts with an assumption that we need this particular tool, that the purpose which this tool addresses should be our main priority at this point in time.

The best questions – the ones that lead us forward – are the ones that seek answers to business objectives independently of technology:

  • „How can we understand and satisfy customer needs more effectively?“
  • “How do we improve our marketing processes for finding / winning / keeping customers?”

If we formulate the question this way we are more likely to select and use technology in an effective manner.

So our first priority is to develop a clear vision of what we want to achieve. Once we have that, we can explore the most appropriate technologies for implementation. For example:

  • „how do we structure offline interactions with prospects and customers so that they generate data that can be measured and analysed?“
  • “how can we combine the data from both online and offline interactions to create more efficient / effective marketing processes?”

The expression „form follows function“ sums up centuries of experience in architecture and design. I believe Marketers today need a similar credo.

Technology follows business objectives“ reminds us to focus on the goals, rather than being distracted by the means.


(1) „Marketingstudie im technischen Mittelstand – Maschinenbau“, Saxoprint Branchenbericht 2016, Seite 8

(2) Over 5.000 at the last count by Scott Brinker:

(3) „Marketingstudie im technischen Mittelstand – Maschinenbau“, Saxoprint Branchenbericht 2016, Seite 12, 14 und 17

Neun Gründe, warum Menschen wichtiger sind als Technik

Die Digitalisierung des B2B-Marketings scheint bei den deutschen mittelständischen Fertigungsunternehmen (Mittelstand) etwas an Schwung verloren zu haben. Es mag sich wie ein regionales Problem anhören, ist es aber nicht; es ist in der Tat symptomatisch für einen globalen Trend. “Warum?” ist eine interessante Frage. Sinnvoller ist es aber, sich zu fragen: “Was kann man dagegen tun?”.


  • Die CMOs werden schneller vorankommen und mehr Nutzen aus der Digitalisierung von
  • B2B Marketing, wenn sie ihren Fokus von der Technologie auf den Menschen verlagern.

Warum? Probleme mit der Technologie

1. Wir haben schon genug Technologie.

Die anekdotischen Beweise deuten darauf hin, dass die meisten B2B-Organisationen bereits über alle Technologien verfügen, die sie benötigen: eine Website mit Content-Management-System plus Analytik, Suchwerkzeuge zur Optimierung der organischen Auffindbarkeit, Werbe- oder Social-Media-Sites zur Maximierung der Reichweite, E-Mail-Systeme zur Pflege und Outbound-Kommunikation, vielleicht sogar ein CRM, das in das ERP-System integriert ist. Sie haben oft noch viel mehr als das.

Der Marktforschungsbericht von Saxoprint zum Thema Marketing im Mittelstand zeigt, dass Online-Marketing einen wachsenden Anteil am Marketingbudget einnimmt: derzeit 24% und in zwei Jahren auf 33% steigen wird.

2. Wir brauchen nicht mehr Technologie.

Der Anteil der Unternehmen, die aus ihrem derzeitigen System herausgewachsen sind und tatsächlich zusätzliche Funktionen benötigen, ist sehr gering. Die Realität sieht so aus, dass – für die meisten Unternehmen – die Funktionalität aktueller Online-Marketing-Systeme nicht voll ausgeschöpft wird. In der Tat, mit zu vielen Systemen kann tatsächlich Probleme verursachen. “Datensilos und mangelnde Datenqualität stehen einer besseren digitalen Kundenbeziehung oft im Wege”, berichtete ComputerWoche im April 2017.

Häufige Beanstandungen sind, dass die Daten in Silos gespeichert, dupliziert, von geringer Qualität, redundant oder nicht in den abteilungsübergreifenden Informationsfluss integriert werden können.

3. Der Technologiewechsel ist mit hohen Kosten verbunden.

Der Umstieg auf ein neues System ist mit Duplizierung und Übergang verbunden. Zuerst die Kosten für den Parallelbetrieb von zwei Systemen für zwei, wenn nicht sogar drei Viertel, bevor das alte System abgeschaltet werden kann. Hinzu kommen Fragen des Change Managements: die direkten Kosten der Umschulung von Anwendern in verschiedenen Systemen und der Verlust an Effizienz bei der Definition neuer Geschäftsprozesse und dem Erlernen neuer Arbeitsgewohnheiten. Dies ist kein Weg, den man auf die leichte Schulter nehmen sollte.

Implikationen für Menschen

4. Digitale Einhörner und andere Fabelwesen

Im Jahr 2017 steigt die Nachfrage nach Digital Marketers, die Expertenstatus in mehreren Online-Toolsets haben. Zum Beispiel Stellenanzeigen, die nach “SEO plus PPC plus CMS plus CMS plus eMail plus Erstellung von Inhalten für Blogs und Social Sites” suchen. Die Realität sieht so aus, dass jeder dieser Bereiche eine Spezialisierung für sich ist. Ist das also eine vernünftige Erwartung? Nun, das ist eine ganz andere Sache.

Die deutsche Sprache hat einen Ausdruck, der es wirklich gut zusammenfasst: das “eierlegendes Wollmilchschwein”. ist natürlich völlig imaginär. Auch der englische Ausdruck “Jack of all trades, Master of none” kommt mir in den Sinn.

Ein globales Problem

Bisher habe ich über den deutschen Mittelstand gesprochen. Doch ein Bericht des CEB (eine globale, forschungsbasierte Organisation, die jetzt im Besitz von Gartner ist) aus dem Jahr 2017 zeigt, dass dieses Muster weitaus weiterverbreitet ist.

In ihrem Bericht “2017-18 Marketing Talent Trends” stellt die CEB einen “robusten Anstieg” der Investitionen in Systeme und Technologie in den letzten drei Jahren fest (derzeit zwischen 7% und 10% des Gesamtbudgets). Der größte Teil davon, so CEB, fließt in digitale Investitionen, “vor allem in die Personalisierung”.

Aber nützt die ganze Investition etwas? CEB: “Unsere Daten für 2017 zeigen in den letzten drei Jahren wenig bis gar keine Verbesserung des Kernverständnisses der Vermarkter für die digitale Landschaft”.

CEB forderte die Marketer auf, sechs Barrieren für organisatorische Marketing-Exzellenz zu bewerten und kam zu diesem Ergebnis:

„Die am wenigsten zitierte Barriere war die Verfügbarkeit von Marketinginstrumenten. Im Wesentlichen sagen uns die Marketingspezialisten, dass sie nicht mehr Daten, mehr Maschinen oder mehr Systeme benötigen, sondern dass sie sich weiterbilden müssen, um die Tools, die sie bereits haben, nutzen zu können.“

Es ist nicht einfach, dies abzuschwächen: Die Informationen der CEB basieren auf der Untersuchung ihrer Mitgliedschaft und ihre Präsenzen in allen wichtigen Volkswirtschaften. Das Unternehmen gibt eine globale Umfragegröße von 93.000 Befragten für diese Informationen an.

Chancen für Ihr Unternehmen

Die Bereitschaft, den Kauf neuer Technologien in Erwägung zu ziehen oder die Möglichkeit, neue Mitarbeiter zu gewinnen, zeigt, dass der Schmerz, den Marketing-Direktoren empfinden, sehr real ist. Aber, wie wir gesehen haben, sind diese Standardantworten – neue Software und / oder zusätzliches Personal – unwahrscheinlich, um die Probleme zu lösen.
Wie kommen Sie – als CMO eines mittelständischen Herstellers – bei der Digitalisierung des Marketings erfolgreich voran?

5. Nutzen Sie die Technologie, die Sie bereits besitzen, effektiver.

Dies ist sicherlich ein vernünftiger Ausgangspunkt. Die Schlüsselfragen, die es zu stellen gilt, sind – in der Reihenfolge der Raffinesse:

  • Wie kann man das Beste aus den einzelnen Technologien herausholen?
  • Wie können sie kombiniert werden, um bestimmte Aufgaben effektiver zu erfüllen?
  • Wie kann man Aufgaben neugestalten, um Geschäftsziele effektiver zu erreichen?

Diese Ansätze beginnen, den Fokus von der Technologie auf die Art und Weise zu verlagern, wie wir sie nutzen, aber um sie funktionieren zu lassen, müssen sie greifbarer sein…

Vielleicht ist es an der Zeit, noch konkreter zu werden und zwei weitere Wege zu beschreiten:

6. Erhöhung des Budgets für externe Agenturen.

In hochspezialisierten und fachkundigen Bereichen wie SEO und Online-Werbung können unerfahrene Mitarbeiter kurzfristig sogar Ihr Unternehmensranking, Rating, Score etc. schädigen und Sie langfristig kosten.

Die Erhöhung der Budgets für Agenturen ist daher nicht nur der schnellste, sondern auch der sicherste Weg, um das Volumen zu steigern oder die Reichweite des Marketings in kurzer Zeit zu erhöhen. Das bevorstehende EU-Datenschutzgesetz ist ein weiterer Bereich, in dem Risikobereitschaft eine falsche Wirtschaft ist. Ein kleines Budget für externe Beratung kann der Marketingabteilung Zeit und Ansehen ersparen – und möglicherweise auch viel Geld.

7. Investieren Sie in den produktiven Wert Ihrer derzeitigen Marketingmitarbeiter.

Produktbasierte Anwenderschulungen helfen den Mitarbeitern, mit einem Werkzeug effizienter zu werden, aber sie bringen Sie nur so weit in die Effektivität. Was Unternehmen wirklich brauchen, ist ein praktischer Wissenstransfer von sehr erfahrenen Außenstehenden, die mit Ihren Mitarbeitern vor Ort zusammenarbeiten. Durch die Zusammenarbeit in konkreten Projekten können Ihre Mitarbeiter schnell und effektiv Best Practices erwerben, die sie in Top-Unternehmen erlernt haben.

Die Online-Marketing-Prozesse, die ich beispielsweise im Rahmen eines zehntägigen Wissenstransferprojektes für einen Kunden konzipiert habe, wurden sechs Jahre lang monatlich konsequent eingesetzt. Diese Art des Engagements stellt oft eine sehr effektive Investition dar.

Was wir tun müssen, um die Effektivität des Marketings zu erhöhen.

Um die Digitalisierung des Marketings auf die nächste Stufe der Effektivität zu heben, müssen die CMOs meiner Meinung nach ihre Aufmerksamkeit von der Technologie auf die Menschen verlagern.
Genauer gesagt, in mittelständischen Unternehmen, die keine großen Marketing-Teams haben, wird es lebenswichtig wichtig, zwei Schlüsselthemen zu entscheiden:

  • welche Technologien erfolgskritisch sind und welche nicht;
  • welche Fähigkeiten im eigenen Haus bleiben sollen und welche nicht.

Was ich vorschlagen werde, klingt vielleicht nicht eingängig:

8. Die Implementierung der geschäftskritischen Technologien sollten ausgelagert werden.

Wir sollten dem neuen Nachwuchskräfte Hans (oder Gretel) Alleskönner nicht die praktische Verantwortung für vier geschäftskritische Technologien anvertrauen, in der naiven Hoffnung, dass sie in allen vier Bereichen mit einer maximalen Mittelausstattung von jeweils 25 % VZÄ Ergebnisse in A1-Qualität liefern können.

Stattdessen sollten wir uns mit spezialisierten Agenturen zusammenschließen, die sich jeweils auf ein einzelnes Gebiet konzentrieren. Auf diese Weise wird sichergestellt, dass das Volumen bei Bedarf erhöht werden kann. Sie sorgt auch dafür, dass die Tätigkeit das ganze Jahr über fortgesetzt wird, ohne Unterbrechung durch Berufsausbildung, Urlaub oder Krankheit.

Technologiebasierte Fähigkeiten sind nur eine Möglichkeit der Digitalisierung. In der Praxis sind zusätzliche Kenntnisse erforderlich.

9. Die Fähigkeiten, die intern bleiben müssen, sind diejenigen, die wir noch nicht aufgebaut haben.

Der CEB-Bericht forderte Marketers auf, sechs individuelle Barrieren (im Gegensatz zu Unternehmensbarrieren) für Marketing-Exzellenz zu bewerten. Die beiden Top-Themen sind “Bessere Definition individueller Rollen und Verantwortlichkeiten” und “Verstärkte Zusammenarbeit zwischen den Teams”. Die CEB zitiert erneut eine Stichprobengröße von 93.000 Befragten für diese Informationen.

Die Aufgabe, die es zu erledigen gilt, ist also eine Aufgabe, mit der die CMOs jetzt beginnen können: die Befähigung der Menschen. Meiner Ansicht nach bedeutet dies einen schrittweisen internen Übergang vom „Machen und Tun“ zum „Verantwortlichkeit für Prozessen”.

Meine eigene Erfahrung ist, dass die Menschen die Herausforderung lieben, die Verantwortung für Prozesse, die Gestaltung von Workflows zu übernehmen, sinnvolle KPIs mit anderen Teams oder Abteilungen zu diskutieren und abzustimmen, Berichte zu interpretieren (von spezialisierten Agenturen erstellt), Erkenntnisse zu gewinnen, die zur iterativen Verbesserung von Prozessen genutzt werden können… Kurz gesagt, eine geschlossene Feedback-Schleife für eine lernende Organisation zu schaffen.

Wer sind die besten Kandidaten für diese Positionen? IMO, nicht das Personal externer Agenturen. (Dies ist keine Reflexion über ihre Kompetenz, sondern lediglich eine Unternehmenspräferenz. Hier finden etablierte und vertrauenswürdige Inhouse-Mitarbeiter Platz, um ihre neuen Aufgaben in der digitalen Wirtschaft wahrzunehmen. Ihr Wert für das Unternehmen liegt in der Erfahrung mit Produkten, Kunden und Prozessen, und diese Erfahrung ist ein Kapital, das es zu pflegen und zu erhalten gilt.

Gleichzeitig müssen vertrauliche Informationen des Unternehmens intern bleiben. Der Übergang vom „Machen und Tun“ zum „Verantwortlichkeit für Prozessen” stellt sicher, dass beide Ziele erreicht werden.

Stimmen Sie diese Ideen zu?
Kommentare und Rückmeldungen sind willkommen….

 * Der “Digitalisierungsindex” in deutschen mittelständischen Unternehmen wird von TechConsult im Auftrag der Deutschen Telekomm recherchiert. Die Ergebnisse für das produzierende Gewerbe zeigen für die Bereiche “Kundenbeziehungen” und “Digitale Angebote und Geschäftsmodelle” keine Veränderung von 2016 bis 2017. Demgegenüber verbesserte sich der Bereich “Unternehmensproduktivität” gegenüber 2016 um 3 Punkte auf 58/100 im Jahr 2017, während der Index für “IT-Sicherheit und Datenschutz” um 2 Punkte auf 68/100 zulegte.