From Keywords
To Powerful Product Descriptions

How To Systematically Create & Automate Customer-Oriented Content
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From keyword to powerful product descriptions
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About the Whitepaper

Do you know your target group and what your customers really want? Success in e-commerce is all about answering the following questions: Who are potential customers? What do they want to know about the products they are looking for? What contributes to their eventual purchase decision?

So, what should e-commerce businesses do to better understand their customers? This white paper gives you an in-depth guideline on:
- How to find out the search intent of (potential) customers
- How to create high-quality content on the basis of the search intents, that helps customers to make a purchase decision
- How the “content lake” strategy helps businesses to provide customers with the best possible user experience


Norman Nielsen

Norman Nielsen

Vice President Growth, OMIO

Norman Nielsen is Vice President Growth (SEO, CRM, ASO, Content Marketing) at the international travel platform OMIO and works with colleagues from over 40 different nations. Prior to that, he spent 6.5 years building the global SEO and content marketing team at Zalando and the SEO at Axel Springer's real estate portal. He is considered a specialist in international search engine optimization, innovation management and global teams. As an independent consultant, Norman supports global companies in their digital strategy and online
 marketing. He was educated on 3 continents and has 16 years of experience in e- commerce for international companies.

Following the motto "people first, but product second", Norman sees the future success for e-commerce companies in the ability to derive personalized, automated, and user-centric products from data and to quickly put out these products on the international market.

First Look into the Whitepaper

From Keyword To Search Intent

Keyword analysis

The keyword analysis serves as a strategic element for gaining insights into the search behavior of users that use search engines. The terms the user searches for in a search engine are identified, divided into certain groups, and their search frequency is recorded.
Further useful metrics in the keyword analysis, however, we do not go into more detail here, are: seasonal trend analyses, the CPC, estimated clicks, competition density and elements of the search results page (SERP).
The German search engine market is dominated by Google. Statista reports that the search engine holds a share of about 83% of desktop searches and around 97% of mobile internet searches.
Companies that are operating online outside of Germany and the EU are advised to look into search engines such as Bing, Baidu, Yandex, Naver, DuckDuckGo and Ecosia. Baidu is particularly dominant in China and offers its own tools for
performance analysis.
The keywords can generally be divided into short-tail, mid-tail and long-tail types.

Short-tail keywords typically contain one or two words, consist of very general
search terms, and are often searched for with a higher volume of competition.

Long-tail keywords, on the other hand, have a lower search volume, yet are much more specific. They have lower competition and in some cases lower CPCs as well as higher conversion rates.
It is fundamental to analyze the set of keywords used by potential online customers and the resulting information architecture for content generation.
Information architecture includes, for instance, internal linking, required page types as well as filters and the resulting analysis of the intention underlying the search query, the search intent.

The first steps of keyword analysis

For your first steps of the keyword analysis, start with one or a combination of several tools from the list below:
1. Free tools
Ubersuggest,,, answerthepublic
2. Fee-based tools, Searchmetrics, ahrefs, SEMRush, xovi
3. Google Tools
Google Keyword Planner, Google Trends, Google Search Console,
related search queries
4. Various tools & processes
Analyze competition content, interview suppliers, interview & brainstorm ideas with experts, combination of all product and category keywords including all filters, followed by a search volume check for each possible combination.

A helpful approach has been to group the keywords into topic buckets (topic 1 clusters, or also called topic areas). - this creates a logical link between a superior topic area and the different keywords (e.g. women's shoes: high heels, ballerinas, women's sneakers, women's boots, etc.).

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