Analytics: Methoden zur Vorhersage des Kundenverhaltens

  • Beitrags-Kategorie:Analytics

Sehr interessanter Artikel hier über Predictive Customer Behaviour.

As with anything new, you start small and work your way up. Here are some ideas:
1. Study One Factor — Using basic spreadsheet software, study historic trends in your business to forecast expected revenue tomorrow, next week, or next year, which is useful for setting budgets and goals. Data scientists call this kind of analysis “univariate time series” because you look at only one variable over time, ignoring how other factors might come into play. For example, you might look at the timing of offers you have made and how well they have done.
2. Study Two Factors — Begin using what is called “correlation analysis” to predict customer behavior, and start gaining control over future revenue. Correlation analysis looks at two trends or factors to see how they relate and whether one might be able to predict the other. You can use ordinary spreadsheet software. For example, you might add holidays and the school-year calendar to your analysis in step one. Then, you may notice a correlation between the start of spring break and how successful your offer was. You see the opportunity to make timing decisions regarding your offers that take into account a greater awareness of the customer’s needs.
3. Study Three or More Factors — Known as “multivariate regression,” some of this can be done with spreadsheets, but at this stage, most companies turn to specialized data-driven marketing software. Most spreadsheet software has limitations; if your software lets you have a million rows, it will not be enough if you have 10 million customers. But here, you can start to see the power this analysis can bring to the table. Using our example above, what if you added household income, number of children, and children’s ages to the analysis? You can see how you could more accurately target your ideal customer and properly allocate precious marketing resources.
4. Leverage Real-Time Data — Imagine using multivariate analysis based on data collected in real time, predicting customers’ behaviors instantly, and delivering the appropriate content at the moment they need to see it. This is the most advanced level of analysis, and it only scratches the surface of what is possible.

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