#datadrivenPR – How to turn Data into Stories

#datadrivenPR - How data becomes stories

Daten PR

Abb.1: Zauberkugel der Mini Playback Show

Abb.1: Zauberkugel der Mini Playback Show
Abb.2 Cotton Made in Afrika, Initiative der OTTO Group

Abb.2 Cotton Made in Afrika, Initiative der OTTO Group
Abb.3 Isabelle Ewald zeigt den Streitatlas der advoCard

Abb.3 Isabelle Ewald zeigt den Streitatlas der advoCard

“Dates are cold and unemotional by their very nature.” With this sentence Isabelle Ewald started last Wednesday’s workshop on “Data-driven PR – How data becomes stories”.

So how does that fit together? Cold data and compelling PR stories? Very well indeed! Isabelle immediately sent us back to the 1990s. Who of us 90’s kids didn’t dream of getting into the magic bullet with Marajke Amado (see fig.1).

Data PR is the magic bullet of communication.

According to Isabelle, the magic bullet is a great metaphor for data PR. Apparently boring, perfectly normal children hold an interview with the presenter: “What are your hobbies? – Reading and playing soccer.” Sounds like the average kid at first glance, so not very exciting. But then they get into the magic bullet and come out – TADAA – totally transformed, dressed up (okay, from today’s point of view a bit questionable…) and somehow more exciting. According to Isabelle, that’s exactly how it works with data-driven PR.

Every company has data. And even if this data is sensitive and should not be published, you can still access huge data pools of third party providers like open data portals, market research companies or foundations. Or you can simply collect the data yourself using your own surveys. Here, one should only consider that it is often only a ” brief sentiment picture” and the survey is not representative.

Data PR thus describes the systematic use of data in communication work in order to convey (usually complex topics) in a targeted manner, to explain them better and to create a context. Data can either be the tool used to tell a story, the source on which a story is based or both. There are many ways to visualize the story.

As an example, Isabelle presented the OTTO Group’s “Cotton Made in Africa” (CmiA) initiative (see Fig.2). This is a very good illustration of what can also be done with a small amount of data. Actually, there were only two figures in the beginning:

  1. Quantity of “CmiA” cotton used by the OTTO Group –> 16,000 t
  2. Resulting amount of water saved compared to the production of conventional cotton –> 33 billion litres

That sounds like a huge amount to be said at first. But how much is that anyway? So we need a good comparison to illustrate to everyone what an enormous amount of water has been saved here. The per capita water consumption of a person living in Germany was used as a comparison. That corresponds to 750,000 people. And now we simply looked at the number of inhabitants with which this figure can be compared on the basis of major German cities. And suddenly the cold figures and enormous dimensions become clear, obvious and comprehensible for everyone.

This data PR example also pays off in an essential part of good public relations: proximity. Besides topicality and importance, proximity is a key news value. Everyone is interested in what is happening on their own doorstep. This is why, for example, the annual dispute atlas of advoCard, the burglary radar of the Hanover police department or the salary check of the BILD newspaper work so well.

From Data Set to Data Treasure

The attentive reader could of course ask himself the questions now: What is this all about? The sweatpants atlas? These are just entertaining stories without any added value?

Entertaining: Yes. Without any added value: No (see below). Data-driven PR stories are predestined for online content. It’s about little stories or snippets that make you smile and then you forget about them 10 minutes later. But that’s okay. If you take a look at the flood of information on the Internet and especially in social media, it quickly becomes clear: It’s not about the big story! It’s about the many little stories that move us, that perhaps have a direct connection to us or our lives.

Of course you can also evaluate large-scale market research and generate data PR from it, but good data PR does not necessarily have to be associated with high costs. Rather, good data-driven public relations is a highly collaborative topic. You have to build a network. Often you have a particular question, but you can’t answer it with your own resources and powers. Therefore, you should think in advance about what data I need to answer my question and then ask in the appropriate department (e.g. Business Intelligence) or pull the corresponding data set from the network. Without cooperation, nothing works and good data PR depends on many competences.

What added value does data PR have?

Digital Reputation

Data-based PR stories sharpen the “digital image” of companies and organizations, stand for long-term vision.

Transcultural Effectiveness

Data PR is largely language-independent. In a very short time you get a rough estimate of what it is all about (e.g. seat allocation in the Bundestag).

Transparency

Data create transparency and make complex topics “touchable” and comprehensible.

Uniqueness

(Own) data are available and cannot be found in this form anywhere else. They are exclusive.

Online First

Data-based PR stories are predestined for online content and have a high degree of “shareability”.

(Data)Pearl Diving Made Easy

In order to present data as clearly as possible, there are different formats that work very well. Listicals (“10 tips for…”), for example, are currently in great demand. But watch out for too much click-baiting according to the scheme “No. 8 will blow your mind! A barometer, such as a mood barometer, for example, is well suited for a database that is based on a monthly period. Infographics had a big hype a few years ago and typologies are almost psychological. With an index you can illustrate very nicely where a trend is going and an atlas is a nice visualization, especially as a heatmap.

Formats that work:

Preparation of regionalisable data on emotionally gripping topics; presentation as a map.

Indicator based on certain characteristic values, which shows trends and developments.

Classification of people into groups based on certain social parameters.

Efficient communication of facts with a focus on clarity, accuracy and vividness.

Listed article containing essential facts on a specific topic.

Statistical measuring instrument for recording current sentiments.

And do I need a graphic designer for this?

The good news is: No! There are tools, tools, tools. Here are a few tips for visualizing your data:

Predictive Analytics: Making predictions from data

Bendix Sältz and Dr. Christoph Ölschläger

In the last picalike workshop the data analysts and scientists Bendix Sältz and his colleague Dr. Christoph Ölschläger took us into the world of data, analysis and statistics. The topic “Predictive Analytics with Python” was not only discussed in theory, but we also started directly via Jupyter Lab with data analysis in Python.

These 4 steps should be followed for a good “prediction”:

  1. First of all, one must think of a specific question: What question do I want to answer with my analysis? When I am clear about my actual goal, I need to collect the right data. Everyone talks about big data, but I often don’t need the bulk of the data for my question. Therefore I have to “collect” or request exactly the data I actually need for my analysis.
  2. The second step is to clean up the data. In the workshop we worked on a CSV. We read the data and eliminated all information that did not seem important for our question. Afterwards we processed the data in a way that we had actual values for each field of the CSV that we could work with. So for example we “decoded” text fields.
  3. Depending on the question, we then decided on a model and framework to answer it. In the workshop we talked about the random forest and about different regression models, such as the linear regression model.
  4. In the fourth step, the model must then be interpreted to derive a prediction. This prediction should then be prepared visually and entered in a presentation that is easy to understand (not only for statisticians).
4 steps to prediction

It is a capital mistake to theorize before one has data.

Sherlock Holmes, “A Study in Scarlett” (Sir Arthur Conan Doyle)

And here are our Top 4 Take Aways straight from the workshop:

  1. Data processing takes time
    Without clean data, no good model can be created. Clean data is absolutely necessary to understand the problem. This takes time, but must be done.
  2. Not always good models
    A good model cannot be built on all data sets, no matter how large they are. Sometimes the predictors are not meaningful.
  3. The more data, the better
    Small data sets are subject to greater fluctuations (law of large numbers). But: Large data make handling more difficult.
  4. Accept disappointments
    Sometimes you can turn a dataset back and forth as often as you like: It is simply not possible to make any specific predictions about the initial question. But: By analyzing the data, you can still gain insights into many things and you can draw your own conclusions and possibly answer a different question.

Growth Hacking – Between Buzzword and relevant Marketing Tool

Growth Hacking - Between buzzword and relevant marketing tool

What actually is growth hacking? What’s behind this buzzword? How do you use it and how do you become a sought-after growth hacker yourself?

Andreas Anding answered these and many more questions at a workshop on “Growth Hacking” last month. Andreas is the CEO of Remote Native GmbH, a digital expert and consultant with extensive know-how in marketing, sales and technology.

The special thing about this workshop was – and maybe you can even call it Growth Hack – that this time it was not only about pure theory, equipped with general use cases, but was a real team event. In advance, each participant could submit case studies of their companies. These case studies were then discussed in small groups of 4-5 people and they looked at which growth hacking methods could be applied to these concrete company examples in order to create more growth, more awareness.

The case studies came, for example, from P&C Nord with its online shop VanGraaf.com, adSoul, Endereco GmbH, Traveldude and of course picalike itself.

The composition of the teams with people from very different companies and from different areas has given us a rather ingenious departure from the standard program that you normally drive in marketing. I really enjoyed that. – Thomas Ziegler from Adsoul

Growth Hacking Workshop mit Andreas Anding

Which methods can be used to generate growth?

There are numerous methods to generate “growth hacking”-like dynamic processes. Here are a few examples:

  • Referral Programs: Clients refer the brand. Customers and new customers are rewarded. For example, the cloud service dropbox became very popular.
  • Influencer Marketing: Which people already have a high reach in the relevant industry? How can they be used to grow the brand? YouTuber and Instagramer are particularly suitable for this.
  • Email Marketing: Can we create content that customers want in their inbox every day? And then share it? Like the briefings that some editors-in-chief send out every day?
  • Social Sharing: How can we turn our customers into brand ambassadors? Like letting their friends know that they are using our product? Like the music service Spotify, for example?
  • Application Programming Interfaces? (API’s): Can we set up interfaces to our content so that web developers can integrate it into their projects? For example, a bestseller list that then appears on other websites, blogs or social networks to promote your product.
  • Viral content: Which content can be used virally – and which not. This concerns the topics, the lines, the texts, the images. If you want to be successful in growth hacking, you need such content.

Creating your own Growth Hack is the true supreme discipline.

Workshop: Strategic Competitive Intelligence

Strategic competitive analysis

As much as you would like to plan the next steps ahead, sometimes someone or, in this case, “something” simply upsets your plans. This was the case last friday, when our workshop speaker Johannes Deltl got stuck at the Vienna airport and unfortunately landed with a delay in the far north. But as it turned out, the wait was worth it! Johannes is a real professional in the field of “strategic competitive intelligence”. As managing director of the consulting firm Acrasio, he can look back on more than 20 years of professional experience on the client and consultant side. As an author, university lecturer and speaker, the native Viennese explained to us, among other things, about the competitive intelligence process, evaluation possibilities and approaches in very different industries. With a short “hands-on” part from the agile project management area, the method of prioritization was illustrated.

Companies should actively consider who could actually become a competitor in the future.

Foresee the next, but also the steps beyond and after the next steps of your competitors, classify and assess them for your own company and then react appropriately. This is what is important in strategic competitive intelligence. With numerous examples, procedures, evaluation possibilities and practical examples from very different industries, Johannes brought us closer to the topic, so that afterwards (over beer, cider and pizza) there was a lively exchange.

Strategic competitive analysis - Johannes Deltl
Group work_workshop_Deltl
Strategic competitive analysis

Interview with the workshop participants

Interview mit Philip von DACAPO (Otto Group)

Hi Philip, introduce yourself for a moment.
My name is Philip and I am currently doing a 6-month internship at the Otto Group in the team of DACAPO. There I do data visualization and machine learning.

What are you studying?
I am studying Quantitative Finance in the Master’s programme in Kiel.

What exactly are your tasks at DACAPO?
Data visualization with tableau. That means I access a database that stores data from crawled online shops and create dashboards that our customers have requested. Or I compile dashboards that we think our customers might be interested in or where customers have already expressed the wish that “this and that” should be displayed. The input for the visualization comes 90% from the customers.

This is basically competitive analysis. And you guys answer questions like: What is the price strategy of my competitors, for example?
Yes, exactly. Or assortments, colours and much more.

And you offer them your dashboard and customers can draw the reports themselves? Or do you send the analyses to them proactively, so to speak?
We provide the data and/or the dashboards to the customers.

What did you take away from today’s workshop?
For me, the whole area of planning and also the evaluation was interesting in the end: What did our tool, which we provide, actually bring to the customer’s decision making or would it be interesting to look at other areas in the future? And to put more work into it together, either internally or together with the customer, to think about what is interesting in the end. Instead of running analyses for days, sending them to the customer and not knowing in the end whether the customer is even interested.

Buch über Strategische Wettbewerbsanalyse

Interview with Adrian from bonprix

Hi, Adrian, introduce yourself for a moment.
My name is Adrian, I come from bonprix and I am a project manager in a department that develops software products for the purchasing and supply chain sector. In other words, all in-house products that are primarily related to purchasing. And currently I am mainly involved in forecasting. That is, demand forecasting at product level.

What kind of lead time you have here?
Different. Ideally, it’s over 6 months. But it all depends. We have different types of products, of course. Some products have been around for over 15 years and they have never changed. However, a very large amount of products are only used once for a single collection and never come back.

How many collections do you have per year?
By now we have reached 12 collections per year, one per month.

What was interesting for you? Why did you come to this workshop?
I heard about this workshop from the head of my department. And it actually fits quite well into this forecasting topic, because of course competition details also play a role. Depending on how many products the competition is currently offering in any way, this can have an influence and we don’t take that into account – at least on this technical level.

That means that you are currently forecasting only on the basis of historical stock data?
Correct.

Is there a topic you find interesting for an upcoming workshop?
Actually everything around product attributes. So which you can possibly also extract from images. After all, these are also responsible for the success of forecasting. So I would be interested to know how much and what you can extract from images.

In other words, at the moment you know what sold very well, but you can’t give a title to it, whether it was the short sleeves or a certain pattern?
No, we also use a lot of attributes, but they are all entered manually and that’s something you could think about to automate. Especially when creating patterns for products, you have to create a lot of attributes for a product that may never see the market. And that is of course
some work. This would also be interesting, for example, that you could get automatic attribute suggestions based on photos.

Fashion Marketing & Predictive Analytics

Fashion Marketing & Predictive Analytics
Last week we were pleased to welcome marketing expert, book author and Professor of Brand Management at the Brand University of Applied Sciences in Hamburg, Germany, Dr. Jörg Igelbrink to our company for the workshop “Fashion Marketing & Predictive Analytics”. In a relaxed atmosphere, Jörg gave us answers to fundamental questions such as..:
  • Is there a basic understanding of the topic “Trend”?
  • At what point do we speak of a “trend”?
  • Which perspectives are relevant?
  • Where, how and when do trends arise that influence the industry?
  • Which success factors influence trends?
  • What role do opinion leaders, early adopters and influencers play in generating trends?
  • How will the demand for our product develop?

With many case studies and expert knowledge from the fashion industry, Jörg was able to bring us closer to this complex topic and even provided some insights from his forthcoming book “Perceived Brand Localness: An Empirical Study of the German Fashion Market (Business Analytics)” (published by Gabler Verlag in December 2019) in cooperation with IBM Cognos Analytics.

After the workshop we had the opportunity to ask Jörg and some workshop participants a few questions.

Workshop: Fashion Marketing & Predictive Analytics 9

Interview with Dr. Jörg Igelbrink

How come you know so much about fashion?
During my time at adidas as Product/Brand Manager I was responsible for the Soccer Department. The players’ equipment is now highly functional. Anatomical cut, breathable Climalite fabrics, capillary effects, etc… The knowledge in this area was the basis for the change to the Business Unit Manager Tennis. At that time tennis became more fashionable. The pure “white sport” became more colourful and fancy with types like Andre Agassi and Anna Kurnikowa. I was responsible for collections for Anna Kurnikowa and discovered my passion for fashion and current trends. The pragmatic eye for sports function has always remained. That’s why the “Athleisure” trend is so exciting.

Workshop: Fashion Marketing & Predictive Analytics 10

Why did you quit your job as a product manager at Adidas and decide to go into teaching and research?
After years in management at adidas, I was budget director at a large advertising agency, responsible for a 20-person team in Hamburg. It is a great pleasure to pass on this practical experience to students and start-up labels. With my dissertation on the perception and consumer attitudes of local brands, I investigate which factors lead consumers to have a positive attitude towards local fashion brands.
What does “trend” mean to you?
In the first moment trend is “increasing quantity over time”. For me, a fashion trend becomes apparent when a larger number of fashion-interested people of opinion leaders, influencers and early adopters adopt a certain product or buying behaviour, which then becomes an attractive self-image in the masses. Recognizing trends from a marketing point of view, i.e. recognizing trends at an early stage in order to generate premium prices for “optimal” market entry, understanding TREND VALUES in order to adapt “marketing”, and TRENDS INFLUENCES in order to expand them and earn them for a long time on the product; these are exciting topics for me! This requires a deep psychological understanding of the consumer and his habits and patterns.

Workshop: Fashion Marketing & Predictive Analytics 11

How important will data-driven marketing be in your eyes?
The topic is very relevant from Big Data’s point of view. In particular, the real-time data generated from social media data is important for customer-oriented marketing control. And also the quality of the information, a more individualized and precise allocation becomes higher. On the one hand, it can be used to analyse buyer behaviour even more precisely, what motivations and attitudes individual consumers have towards a product or service and what demands are made on the product as a result. The information generated from this will produce individual, specific product solutions. But I would like to emphasize that this is not possible without a digital ethical handling of information. This is the only way we will be able to create meaningful solutions in marketing.
How do you see the future of fashion marketing? Where will the journey take us?
The question is too general to be answered in 2 sentences. Basically I see the development in the area of brand development and management as the most challenging in fashion marketing. Against the background of an increasingly digital world and the growing sustainable, ethical demands of consumers, people need to build strong, meaningful brands, maintain them, and design them attractively so that they provide orientation and are a trustworthy partner in their own search for identity. This is what I want in an increasingly complex world.

Interviews with the workshop participants

Interview with Julia from Peek & Cloppenburg

What’s your job title, what’s your position at P&C?
I am responsible for all shop management. This includes merchandising, graphic design, but also shop administration and operation, i.e. the entire shop development at P&C.

What appealed to you about the workshop topic? What was your motivation to come here?
E-commerce and fashion are already special areas. I was with Otto for a long time and I know Sebastian from that. There I also developed the topic “personalization” a lot for the online shop and afterwards I was at Alba Moda. So this fashion theme in combination with predictive is very exciting. Just get a little inspiration and also to talk to you on different levels about “meta-data of pictures”, i.e. visual recognition. So also to look again in this direction, how far you are (Picalike, editor’s note). And I think it’s great that you’re doing such an open round.

Did you like the workshop? What did you think was especially good? What would you have expected a little differently?
Yes, I absolutely liked the workshop. I had actually expected it to be different from the main focus. But I think it’s always very exciting with such a topic how you represent it in terms of numbers. That’s also something we still lack in business. And what really comes, what works, what doesn’t. The speaker has really brought fashion know-how with him, I wouldn’t have expected that in this context. I have to say that I would have expected it to be a little more technical, which is also due to the constellation with you. But I found both perspectives very valuable.

Is there a topic that you would find interesting for a workshop? Is there perhaps an area that you are currently working on that you would like to learn more about?
We actually have the topic “Generate images meta data on the article”. Towards Fashion Cloud, i.e. data generation for the articles. That was also briefly addressed and what you can tap everything in order to collect all data to an article freeware-wise. Perhaps as an idea: If articles are posted in social media, perhaps you can also generate and save data on the article. That would be interesting for us.

And how would you use that? For personalization?
For personalization, for the entire shop control and for content.

Workshop: Fashion Marketing & Predictive Analytics 12

Interview with Sven-Robert from S24.com

Which job title, which position do you have at Shopping24?
I work at Shopping24 as a software developer in the backend area. More in data management than searching now.

What appealed to you about the workshop topic? What was your motivation to come here?
On the one hand, it was interesting for me because I had also worked in the fashion sector before. On the other hand, it’s also interesting from a professional point of view: At the moment fashion24.de is our strongest portal. The data that is collected about it, the data that you need to work with it in order to earn money, to do business is very demanding, but also associated with many possibilities and this is basically an area that offers an incredible number of application possibilities from the programmer’s point of view. It is simply a completely interesting area in itself and also the whole connection with the term “trends”, which is also extremely relevant for us. Besides, I actually had an idea a few days ago for my own little experiment or what I wanted to do, and I was hoping to get some incentives.

Did you like the talk? What did you find particularly good? What did you expect a little differently?
I had thought a bit now, because it’s Picalike, that it also has something to do with computer vision/image analysis. I found the presentation very good, very interesting. I also thought it was obvious that the speaker had practice in it. He is used to speaking in front of people and knows his field. He really transferred competence and it was a top presentation. As if I had attended a good lecture at the university.

Is there a topic that you would find interesting for a workshop? Is there perhaps an area that you are currently working on that you would like to learn more about?
At work I have recently used the opportunity to get to know all areas. Which terms are used in the different teams? An example: When we say “feed”, other people say “app” and when we say “client”, the answers are very different. That’s why I took some time to do my onboarding myself. But apart from that, there are topics such as graph databases. That would be a very interesting topic because of the data structures behind it. What is also interesting, because it will become more and more important in the future, is the GPU programming in Python. So where the calculation is not executed on the processor, but on the graphics card. Such a thing as image analysis is extremely computationally demanding and how can I avoid running my calculations on a cluster of 1000 processors if it were possible with three, but a thick graphics card is in it.

Customer Journey: The cornerstones of a detailed customer analysis

Customer Journey: The cornerstones of a detailed customer analysis

At yesterday’s workshop on “Customer Journey: The cornerstones of a detailed customer analysis” we welcomed Akanoo managing director and digital marketing expert Benjamin Ferreau. 17 participants gathered on our premises and listened with interest to Benjamin’s presentation. From the beginnings of the Customer Journey (medieval marketplaces, retail stores, catalogues) to intelligent, data-driven customer communication. Ultimately, it doesn’t matter where the customer is and where the conversion takes place.

From electronic-Commerce to everywhere-Commerce.

The Customer Journey is subject to an evolution of customer relations and customer approach. On the basis of customer behavior, the optimal approach is chosen to create an online experience. Different Omni-Channel concepts can be pursued (Hint: Only betting on vouchers is not so cool). Rather, the customer experience must also be extended by non-monetary campaigns.

Workshop: Customer Journey - Die Eckpfeiler einer detaillierten Kundenanalyse

The Customer Journey becomes the Customer Interest Journey.

The use of artificial intelligence in modern customer journeys is of decisive importance. Only with the help of data can the needs of so-called unknown customers be understood and satisfied. Previously, AI was able to analyze customer behavior and derive forecasts and target customers from it, but always on the basis of historical data. But AI and Omni-Channel have reached a new level of evolution. Now the AI can determine customer behavior in real time and continuously optimize it. This avoids rigid categorization and focuses on the individual customer.

Everywhere-Commerce simply does not take place yet.

Real Omni-Channel plays an essential role to extend the experience. Unfortunately, real Omni-Channel does not take place in Germany at all. It is still thought too much in individual silos with isolated KPI’s, instead of an all-embracing experience to create an Everywhere-Commerce.

We have picked out these 3 Key Learnings for you:

The focus goes from classic eCommerce to channel-independent everywhere-Commerce. Retailers must also make organizational changes in order to better dovetail individual channels and be accessible to customers at all levels.

In addition to macro transactions (conversions), micro transactions (impressions, referrals, baskets, etc.) should also be intensively monitored and optimized. This may help to find new ways to communicate better with customers and to motivate them to convert.

3. in order not to educate customers as discount hunters and thus become price dependent, mainly non-monetary measures should be developed in order to improve the customer experience.

Interview with Benjamin Ferreau

 

Benjamin Ferreau talks about the Customer Journey

Interview with Benjamin Ferreau

What brought you north as a Swabian?
After studying industrial engineering, I came to the north for the job. I worked there for the EversFrank-Media Group, Germany’s second largest print and media group. There I mainly dealt with corporate development, digitization, mergers and acquisitions. Since 2017 I have been Managing Director of Akanoo, a digital technology agency.

What exactly are you doing at Akanoo? What does your daily work look like?
I am the managing director and responsible for strategy, finance, investor search, stake and shareholder management as well as sales and marketing at Akanoo. As managing director, I don’t really have a real everyday working life. I always start relatively early, between 7.00 and 7.30 and try to start with administrative topics. During the day I am usually on the road. In the evening I try to keep my rhythm again and to complete administrative tasks again. But there is no real everyday life.

You call yourself a “customer journey optimizer.” What exactly do you mean by that?
Actually, this means the message of Akanoo: We try to support the customer on his way to the conclusion with different anchor points.

What motivated you to work in this field?
Above all the technology, the AI. But also e-commerce and the start-up environment. But the technology was already the decisive point.

What challenges do you see in the fashion industry with the topic “Customer Journey”?
The biggest challenge is actually competition: new brands are cannibalizing the old-established brands. It’s getting harder and harder to survive. Another challenge is clearly the company’s own structure. A major rethink still has to take place here.

How and where do you find out about the industry?
A lot of things happen to me via the network. I am well networked and regularly exchange information about the industry here. But I also read specific platforms, blogs and studies in between.

Where do you think the e-commerce business is going?
I think the marketplace idea will have an enormous impact. For big manufacturers it doesn’t really matter on which platform they sell, but the trade has to represent a certain mass and it gets more and more difficult.

Sandra and Benjamin in conversation

Interviews with workshop participants

Interview with Falko from Zwanzigzehn GmbH

What’s your position at Zwanzigzehn?
I am managing director of Zwanzigzehn GmbH and head of the online shop of myclassico.com.

What do you do in your working life? What exactly does your position involve?
With my agency, I help with the technical and strategic development of online shops and provide advice. We also have SEA measures in our portfolio.

Why are you here? What motivated you to come to this workshop?
I’m hoping for new ways of thinking and perspectives around Customer Journey. Even our customers have not arrived at Everywhere-Commerce and it often helps to recall the individual steps. In this way, we can make the image of Omni-Channel and Everywhere-Commerce clear to the customer, because there is often still a lot of power of persuasion required.

What did you find particularly interesting about the workshop?
The deep insight into the technology as well as the overviews and charts. They always bring you back to the bottom of the facts and clarify what you actually do.

What would you like to know more about?
I’d also like to know where Germany is in the industry mix. What is the general way of thinking about Customer Experience and Omni-Channel? Are other industries already further along?

Die Teilnehmer des Workshops hören gespannt zu

The participants of the workshop are listening eagerly

Interview with Philip and Niklas from OTTO Group

What are your positions at the OTTO Group?
We are Project Managers Customer & User Experience and Process Optimisers.

What do you do in your working life? What exactly do your positions contain?
We have grown historically as a classic service provider and even now we are active within the OTTO Group in an advisory, executive and analytical capacity. Our methodological skills are in demand and we then work as project managers, so to speak. We look at the different contact points of the customer journey, such as the packaging.

Why are you here? What motivated you to come to this workshop?
Basically it is an exciting topic for us and we hope for fresh impulses. It is interesting to look at the topic from a start-up environment. We only ever see it from a corporate perspective. The Customer Journey and the Customer Journey Mapping are essential for our job, but it doesn’t always attract attention. It is still thought too much in silos.

Was the workshop interesting for you and if so, what exactly?
Yes, both the content and the framework in which this workshop will take place is very interesting. On the one hand, we have received new food for thought and new impulses, on the other hand, however, one also finds confirmation in his daily work. Many charts have recently been seen at university. So it’s good to bring this knowledge back to mind. Also the foresighted point of view is interesting, so keyword Everywhere-Commerce. At the OTTO Group, Connected Commerce is also a major issue at the moment. So we take a very similar view. It was also interesting to realize that the voucher is actually dead and that one has to think about new approaches.

What would you like to know more about?
Of course further information about Customer Journey or Customer Experience would be interesting. But also measures for personalization, which have a lot to do with the customer journey, if not even determine it.

Interview with Tobias from Fixson Media GmbH

Kundenansprache und Kanalintegration

What’s your position at Fixson Media?
I am a managing director.

What do you do in your working life? What exactly does your position involve?
Fixson Media is an online media agency. We help bring portals, websites and shops to market.

Why are you here? What motivated you to come to this workshop?
On the one hand because Sebastian is an old friend of mine and he invited me, but on the other hand because the topic is interesting for our agency.

What did you find particularly interesting about the workshop?
We also notice again and again that many companies are not ready, although the technology is there. There is a lack of openness and structure within the companies. This was confirmed again in this workshop. In addition, it was a good mixture of bold, i.e. concrete application examples and definitions. I found slide no. 29 [note: see illustration on the right] particularly interesting: It simply makes it clear that you can’t leave out any evolutionary step and only if you have the data can you get the customer to everywhere-commerce.

What would you like to know more about?
I am actually interested in everything that has to do with corporate development.

Note: The interviews were recorded in the protocol.

Information extraction from websites (focus on product details)

Information extraction from websites

Last Tuesday, a crowd of software developers and data specialists gathered in our company to listen to the words and tips of Timo Schulz. Timo is a former employee of Picalike and now a consultant at ITGAIN Consulting. As a specialist for artificial intelligence and in particular machine learning, deep learning and data processing, Timo advises companies on advanced analytics and AI.

The topic of the workshop, which was attended by 20 participants from different industry sectors, was “Information extraction from websites with a focus on product details”. In other words, how do you get structured data from unstructured texts?

The first part of the workshop dealt with the theory: From RegEx to Neural Networks Timo tried to explain the topic text analysis and text mining to the interested tech professionals and to clarify which problems can be encountered with product texts in e-commerce. After a short break, it was time to get down to business: The laptop keys were actively typed with many “hands-on” examples and a lively exchange took place on learned techniques and new application examples with many tips and tricks.

Afterwards we had a cool beer and a delicious pizza and I had the chance to ask the workshop participants and Timo a few questions.

Interview with Timo Schulz

I’ve always wanted to get more out of data.

 

Where to find which product data and how to process them in a structured way

Where to find which product data and how to process them in a structured way

Why did you decide to work in artificial intelligence?
Already in 2005, during my computer science studies, I started to work with data. I’ve always wanted to get more out of data and did a lot of research in this area. But then I wanted to get out of research and put my knowledge and technology into practice. That’s how I came to Picalike.

Then why did you go to consulting later?
I wanted to get out of the e-commerce business at some point. It was very exhausting and nerve-wracking to bring the technology close to the companies. Often the companies were convinced by the product, the technology, that it worked, but then it partly failed because of political decisions within the company or there was no far-reaching understanding for it. Of course, it is difficult to remain highly motivated. In consulting, I can now advance AI in all areas and show companies without pressure what is possible and how they can implement AI in their companies.

You often have to do a lot of convincing.

What challenges do you see for e-commerce in terms of AI?
The biggest challenge is actually to correctly recognize and assess the potential of AI. And the acceptance: The company has to recognize for itself what AI can do for itself, i.e. for the company. You often have to do a lot of convincing.

Has there ever been a case where you advised a company not to use AI?
No, not really, because AI is so versatile. But sometimes you have to be careful that AI is not just seen as a trend. According to the motto: “We absolutely have to do something with AI now”. Here it is often sufficient to simply structure the existing data in the company better and to see what we can already get out of this data.

As a consultant you should always stay up to date. How and where do you find out about the industry, about new developments in the field?
As far as possible, I dedicate a whole day to research. I read a lot about the topic, follow blogs, listen to lectures by people I follow and then try to implement my own use case as a prototype. So I can then decide whether this approach makes sense in my eyes, whether the topic should be pursued further or not.

The tech professionals are eagerly listening to KI guru Timo Schulz

The tech professionals are eagerly listening to KI guru Timo Schulz

And which trends are exciting at the moment? Where is the journey going?
I think everything about NLU or NLP (Natural Language Understanding or Natural Language Processing, editor’s note) is very interesting and a lot will happen here.

Speaking of language comprehension: I recently read that it has not yet been possible to teach artificial intelligence humor. Is that right?
Yes, it’s not that easy indeed. When, for example, the customer rating in an online shop says: “The shoe is huge, like a VW van.” Then we understand: “Okay, the shoe is most likely quite big. And it was just a bit more fun to paraphrase it.” But the AI would actually compare the shoe with the size of a VW bus. AI just doesn’t think any further. Another example: Jan goes into his bedroom and gets his ball. Then he goes into the garden and puts the ball on the floor. Where is the ball? For the AI it is not clear that the ball is now in the garden.

I heard from a reliable source that you used to be a Picalike beer ambassador. What is your favorite beer and why?
Clearly Sierra Nevada Torpedo. Ken Grossman is a hero! He revolutionized the art of brewing beer. In the 80s he went to Germany and bought a copper brewery there, which he then took back to California. And from then on the beer became simply unbeatable. They use whole hop cones for the beer, not just hop extract as others do, and produce part of their energy themselves via solar energy. When the big California campfires happened, Sierra Nevada brewed a special beer and donated all the proceeds to the victims of the fire

Interviews with the workshop participants

Interview with Lennart from Shopping24.com

 

Interview with Lennart from Shopping24

Interview with Lennart from Shopping24

What is your position at Shopping24?

I am Search Engine Linguistic Manager.

And what exactly do you do in your job?
I help with the processing of search queries. What do users enter as search terms and I take a look at what, for example, linguistically all around it must be captured in order to output the best possible search results.

Why are you in this workshop?
Since I also deal with product texts in my job, I find it interesting to see how information can be extracted there.

Which topics for further workshops would be interesting for you?
In general, I am interested in product search challenges. For example, insights from other website operators who are also involved in product search would be interesting. What challenges do they have and how do they solve certain problems?

Interview with Sarah from AdSoul

What’s your position at AdSoul?
I am a linguist.

And what exactly do you do in your job?
I break down keywords and try to cluster them. A grammatical processing of keywords so to speak.

Why are you here? What are you interested in the workshop for?
First you have to explain what AdSoul does. AdSoul is active in the field of SEM and takes care of automated search engine marketing. Already at university I was involved in text mining and the preparation of data and texts. The goal of AdSoul is basically to create automated text ads sometime. That’s why data extraction is so interesting for me.

Interview with Marc-Olaf from OGDS

What’s your position on the OGDS?
I am a software developer.

And what exactly do you do in your job?
The OGDS is a Company Builder. We identify new and attractive business ideas and build prototypes for them. We provide the operation, the infrastructure and the architecture for these prototypes and I develop the software for them. So basically we provide a technical solution in the area of e-commerce.

Why are you here? What interests you about the workshop?
I’m interested in extracting from texts and I’m interested in what other people are doing in this area, what new ideas are there in this area.

Did you like the workshop and if so, what exactly?
I was primarily here for the exchange, not so much to educate myself professionally because I already know this topic very well. But I think Timo explained the subject very well and captured the breadth of the topic well. This enabled me to draw out interesting ideas and, in part, new perspectives.

Which topics for further workshops would be interesting for you?
I am always very project-driven. At the moment I am very interested in the topic extraction of data from pictures. Therefore I am also happy if I can exchange myself with Picalike on this topic.

Interview with Erwin from Shopping24.com

 

Interview with Erwin from Shopping24

Interview with Erwin from Shopping24.com

What is your position at Shopping24?
I am a Java developer.

And what exactly do you do in your job?
I prepare product data in e-commerce. I take care of the product search at Shopping24 and the support of the back-end systems.

Why are you here? What interests you about the workshop?
On the one hand, I’m here to expand my own knowledge. On the other hand, at Shopping24 we use product feeds. The aim here could be to extract text from external websites without feeds.

Editor’s note: The interviews were recorded in a protocol format.