Uncertainty is a prevalent problem in content marketing, because it is unclear whether investing in content and content optimization actually leads to the desired result.
The reasons for this uncertainty are easily identifiable: Unclear content rankings in the search engine and the competitor behavior that can only be predicted under certain conditions. Every additional article increases the uncertainty. For large content amounts, there is a correspondingly great uncertainty, in terms of which measures and priorities are most appropriate.
At the same time, content marketing and optimization are very complex. The main challenge in content marketing is minimizing existing risks. One way to reduce the uncertainty and minimize risks is to optimize the content on a portfolio level. Compared to optimizing content for a single article, you can control the goals of content marketing better within a portfolio, and thus have better control of the associated risks. In particular, a systematic portfolio approach is very effective. It entails optimizing a large number of articles within an existing content portfolio, based on defined objective criteria.
This article will present several ways in which you can optimize your content portfolio. This includes a discussion about appropriate KPIs, as well as transfer of proven portfolio instruments in content marketing.
The term "content" usually refers to a set of text articles that are accessed by users on a website, online shop, or social media page, and hence lead to contact establishment. If you want to look at the entire content as a portfolio, you must first define the factors that are important for optimization of the portfolio.
Every article can be described in qualitative and quantitative features. One example of a key qualitative feature is the keywords for which the article is optimized. This qualitative attribution is related to quantitative features such as the search volume associated with the keyword, or the average CPC. Such quantitative features have the advantage that they can contribute towards objectification of the portfolio. In addition, they can also be distinguished based on input and output parameters.
The first step in portfolio optimization is to define the relevant goals, i.e. the output parameters.
Possible quantitative objectives include:
From a business perspective, the focus is typically on sales generated with a content object. However, these not only depend on the quality of the content, but also on the price and quality of the offered products, as well as the conversion quality of an online shop.
A distinction must be made between the output-related target parameters and control parameters. You can have a direct influence on these parameters, e.g. through selection of a focus keywords for the optimization. Thus, you should measure the effectiveness of content based on parameters with which the quality of content can be controlled directly in terms of the company’s goals and optimization objectives.
Possible control parameters for the content and keyword quality are the:
Here, optimization of the portfolio becomes all about identifying content objects that have a high optimization potential. At the same time, you should also identify other objects that have a particularly low potential, and keep an eye on them.
To make this selection, the ranking position of an existing object is a good measure of achieved content success. In any case, it is clear that an object which is ranked in the first position has a higher ability to reach a wider range than one placed in the tenth position. Thus, the ranking position is the most important determinant for the actual number of visits achieved through search engine optimization.
However, the ranking alone is not a sufficient indicator. What would be the importance of a ranking in the first position if it currently only has 10 hits? And what good is a top ranking with a high search volume if the keyword does not have any commercial relevance? The commercial relevance of a keyword is in turn reflected on the click price, which is also a good indicator of the competition.
This forms the basis for the next step, which entails defining an effective control parameter based on the "search potential" of the content portfolio, using the following factors:
Here, the search volume and click price in turn give the search value, which is a separate indicator for the attractiveness of a keyword. The achieved ranking position determines how complex it is to achieve the search value.
Mathematically, it is all about determining the optimization potential for the content portfolio. This is right in the middle of two extremes: For a top ranking, there is a high chance of realizing the search value, whereas for a poor, or even no, ranking, there is no chance in participating in the search value of a keyword.
The decisive factor is therefore the ranking position that was achieved before optimization. The poorer this is, the lower the probability of a high search value. On the other hand, the higher the ranking position, the higher the probability of an optimization success.
One indicator in this context is the inverse of the ranking position number squared, multiplied by the search volume. If the ranking position number is very high, the potential to realize a high search volume is almost zero. On the other hand, the search potential is generally higher if the ranking is high and the ranking position number small.
Thus, the search potential is a function of the search value and the ranking position (position number = p):
The numerical example below showing the search potential:
Arranging the entries based on the search potential, and hence the priority, gives the following table:
You should start by optimizing content from articles C, D, F, and H, since they have the highest search position based on the search value and current ranking position. The optimization goal should be to attain the first ranking position, whereby articles A and C no longer need to be optimized.
Therefore, based on the search potential, you can prioritize content within a portfolio in an optimal way for the further optimization of existing content. Typically, existing content portfolios are very extensive (e.g. with a five-digit number on ranked articles), making extensive selection or filtering interesting and helpful.
The ABC analysis from customer management is very well suited, as it allows for a portfolio to be sorted based on the target value. For this, you first find the sum of all values that have reached the target value. Next, you determine the relative proportion of a portfolio element in the sum of the target values. Finally, you sort the portfolio elements based on their share on the total target value and cumulate this share. This gives you a list with the most important elements in the portfolio, which have the most contribution in attaining the target values. These are then classified into categories A, B, and C. A-elements are the most important; C-elements have the least relevance.
The table below shows the ABC analysis for the above numerical example.
Categorizing the articles based on their share of the total search potential can be done according to your own judgment. Normally, the A category would be up to a cumulative value between 75% and 80%, and the C category to a value of 5% or less. B elements are placed between A and C. In the example, the categorization results in five articles for 75% of the search potential, three of which (D, F, and H) should be optimized with a high priority.
The ABC analysis enables you to integrate the well-known Pareto principle in your content marketing and search engine optimization measures. More sophisticated and complex analyses are also conceivable, but this should not be the sole purpose of this form of portfolio analysis. Optimization should be the main task supported by the ABC analysis.
Published on 12/20/2016 by Dominik Große Holtforth.
Prof. Dr. Dominik Große Holtforth teaches business studies and media management at Fresenius University of Applied Sciences in Cologne. He is also head of the e-Commerce department which deals with strategy-related questions, the controlling of key performance indicators as well as competition strategies in online marketing and e-Commerce. Prof. Große Holtforth is co-founder of the e-Commerce agency Warenkorb.com and founder of the online plant shop “Meine Orangerie.” This is how he combines scientific expertise and practical experience.
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