What are we doing?

• Advanced Conversion Attribution

  We developed a new class of attribution models, focusing on the real interaction between sessions in the customer journey as well as on the on-site engagement – called the Interaction-Type model or IHC attribution model.

  Attribution Product Flyer (PDF – English)

  Brief Case Study (PDF – English)

  Attribution Explained on Football (PDF – German)

  The attribution system is complemented with an interactive dashboard, weekly analysis reports and direct API connections to the core system. The whole system provides insights into the real value generators down to lower levels such as referral domains, individual keywords and ads, etc.
  Product Website:
  Advanced-Attribution.com (in development)

• Predictive Customer Interaction

  For a real optimization of the omni-channel customer communication, we have to go beyond the usual attribution approach and focus the analysis much more on the larger non-converting traffic share. We have build a predictive analytics framework, based on the insights from our interaction type attribution model. The focus is on estimating the current and predicting the future communication/ interaction level of the individual user in his/her sales process. With these insights we can identify the best marketing actions/ touch points to stimulate customer transfers along sales pipeline. This is further used to maximize sales and profit.

• Offline Media Impact Estimation

  Online media campaigns can usually very well be measured at the individual customer level, but what about the influence of offline campaigns such as print, radio or TV? We have developed a variety of models to estimate the influence of offline media on the customer journey and individual behaviors. The goal is to provide our clients with results like: “offline campaigns A and F during period xyz will increase the traffic by 10-15% transactions by 9-12%.”

  Further have we extended our attribution model to incorporate offline actions as probabilistic events to the individual customer journey.

• Advanced Prediction Tools

  We are specialized at building reliable prediction tools for very complex cases.

  Here an example case for price-curve forecasting:
  We have developed a scalable and self-learning forecasting system for dynamic changing price curves. The system is developed for the context of airline tickets or hotel prices, but the algorithms can basically be applied to any setting where products are sold in advance and prices are frequently adjusted, for example car rental, ferries, etc.
  Case Study (PDF – English)

• SEA Bid Optimization

  We’ve developed a cutting-edge SEA/SEM bid optimization tool. The tool applies portfolio optimization techniques similar to financial applications, but the foundation is an extensive bid-performance estimation engine with learning capabilities.

  We also developed tools to estimate position dependent performances of search-engine ads and keywords such as impressions, CTRs, effective CPC and conversion rates. These insights can straight forward be used to SEA control and bidding strategies on daily or hourly level.

• Data-Mining/ Customer Classification

  We are developing tailored data mining and machine learning algorithms to unveil the information hidden in the data. For marketing and sales the goal is usually to analyze customer data in order to predict individual interests and success probabilities of personalized offers or campaign responses. In this context we also worked on social media data with the target to predict additional information and potential response behavior to marketing actions.

  Another application case Individual Ad-Placement Recommendations:
  Task was to find the best advertisement to show to the right customer at the right time. We are developing custom recommendation system for advertising placements for publishers and ad-networks. Our advanced algorithms work on huge datasets and are designed for very fast computation times. The usual goal is to increase the CTR (click-through-rate) or eCPM (effective cost per 1000 impression) of display campaigns and specific creatives.

  Case Study Data-mining on Agriculture data (PDF – English)

• Call Center Staffing

  An application for the optimal workforce planning in a multi-skill service center (agents have to handle in- and outbound calls and emails). The tool combines advanced long-term traffic forecasting and computation of the cost efficient agent staffing with respect to service level targets.

  Case Study (PDF – English)

• Data Analysis Service

  Apart from project specific data analysis work, we offer our clients Statistical Data Analysis as a service:

  – constant analysis of most recent data

  – automated report delivery

  – report adjustments or analysis focus on current needs

  – regular meetings (local, video or by call)

  We are also performing 360° data analysis of your business, combining all kind of different data sources and perspectives to obtain an overall picture of the business. For example combining different areas such as supply, marketing and sales to identify market trends & potentials, internal trends and problems, and to evaluate areas and processes with their influences and performance in the overall picture.

• Decision Support Tools

  Easy-to-use decision support tools tailored to customer needs, according to the system infrastructure and problem requirements. E.g. the end-user interface is a website or also quite often Excel and the back end utilizes more advanced tools such as Python based applications. Some examples are:

  – demand and price forecasting

  – automated market and demand behavior reporting

  – performance reporting of call center agents

  – computation of optimal (balance of costs and information) updating points in integrated systems

We are always interested in:

• highly motivated self-starters with solid analytics backgrounds

• solution-oriented, real world, “down & dirty” problem solvers

To get in contact, send your CV to
jobs@haensel-ams.com