Kategorie: Data Science

In order to understand the business problem, it is necessary to understand the goal of a project or a business (the latter is easy, it is always about making money). As a consequence, there is a hierarchy consisting of

1. Business Goals
2. Goals
3. KPIs
4. Metrics

A goal is where you want to go or what you want to achieve. It is important to define SMART goals, where goals are specific, measureable, attainable, realistic and timeable:

1. Business Goal: Revenue of 1.000.000€ in 2018
2. Goals:
   1. Reduce the Cost per Order to 5€ by Q3/2018
   2. Increase Website Conversion Rate to 2% by Q3/2018
   3. Increase qualified visits to 10.000 unique daily visitors in Q2/2018
3. KPIs:
   1. CPO
   2. CVR
   3. qualified unique visitors/day
4. Metrics
   1. €
   2. %
   3. Sum/day

Goals, KPIs and Metrics are often confused (and everytime this happens, a sweet beautiful unicorn dies). A good way to remember the difference is a journey:

• You want to go drive from Hannover to Hamburg and arrive before 3 pm. This is your goal.
• KPIs are time, speed and maybe GPS coordinates (are you on the right way)
• Metrics are km/h and time

Sometimes, only KPIs are defined but no goals or KPIs are disconnected from goals. In this case, all numbers are great because there is no goal. Or, as Seneca said, If one does not know to which port one is sailing, no wind is favorable.

Next: The Holy Trinity of Data

A typical example of a business problem that can be solved using data is found in (online) marketing. Marketeers always want to know how they can make sure that they reach the right audience and that they can get the biggest bang for the buck, i.e. that they spend less money on marketing in order to increase their margins.

Several customer journey models exist, one of the simplest being AIDA (Awareness, Interest, Desire, Action) where customers are “driven” through a funnel from a first touch point where consumers learn about the product to the last touch point where they buy it.

Several marketing channels exist, and we will go through a few online channels:

• Organic Search: These are the search results that are shown below paid ads if there are any. In order to rank on Google, search optimization techniques are applied, but it can take from a few minutes to several months until a page is listed. Also, there is no guarantee that a site is listed on the first results page where the majority of users will be.
• Paid Search: Search ads are sold in a realtime auction where advertisers bid for their ad to be displayed for a specific keyword
• Display Advertising: Can be booked on a CPM basis or in an auction, usually in programmatic advertising where advertisers bid on an impression, based on the data they have about the user this impression would be shown to
• Affiliate Marketing: Other websites sell a product and receive a commission
• Social such as FB: Works similar to Paid Search, using an auction to determine the price

Since not every website visitor will buy a product, the cost of acquiring a customer is determined by the conversion rate of the website and the cost per click or cost per mille. If the CVR is at 1% and a CPC at 0.10€, it will cost 10€ to acquire the customer to do a first purchase (cost per order). Sometimes, it is ok to spend more on CPO given that the customer may come back and purchase more.

Online marketing is just one area where data science can be applied, and it is actually questionable why a huge proportion of intellectual resources is applied to the question how more consumer goods can be advertised and sold.

A few important terms:

CPC	Cost per Click
CPO	Cost per Order
CPA	Cost per Acquisition
SEO	Search Engine Optimisation
SEA	Search Engine Advertising
CLV	Customer Lifetime Value
CVR	Conversion Rate
CPM	Cost per Mille

While the initial reaction to the question “What do our users/customers want?” often is “Let’s ask them”, this is a difficult task, and it is rarely done well. It is easy to do a survey from a technical perspective, and several free solutions exist. However, asking the right questions to the right people is extremely difficult.