This project consists in students taking on different roles as category manager, inventory manager, or CMO and by analyzing different datasets from procurement services, sales services and datasets from different branches to give insights and recommandations for strategic actions.
My role as a category manager, my analysis is based upon three pilers: sales (revenue and units) by category, inventory level (organize shelving, promotion of goods and meet demands through a clear understanding of customers' requirements) and product performance (promotion, customer type)
The data used in this analysis come from a fast-moving consumer goods company. In this analysis, i used first of all PCA and KMeans techniques to find the number of clusters
possible of customers. And then i read into the details on the different attribution for the elements of segments. Segmentation is about dividing a population into groups with similar
characteristics: comparable purchase behaviors who would react similarly to different marketing activities. We could detect customer behaviors through historic data: purchase frequency, time of
purchase, purchase quantity and product ratings.
Finally i used Logistic regression to predict the possibility of purchase from the predefined customer segments to point out the target group. Targeting is about evaluating potential profits from segments and deciding which segments to focus on. We take into account the segment size, the expected growth and competitors' offerings.
The goal of this project is to investigate selfies as a key consumption practice in digital consumer societies. The questions i was trying to answer to are "What are the different kinds of values that sharing selfies provide?", " What are the consumer cultures expressed by different consumers through that practice", "how are they technologically shaped by apps and platforms?".
The method used is digital immersion. Qualitative analysis of a sample of Instagram selfies about champagne brands, including related metadata. Examining whether and how metrics (e.g. number of favorites) are linked to different types of content; developing a coding scheme and classifying selfies manually; understanding users’ representations of consumer cultures.
Relationship marketing is a facet of CRM
which is nowadays often industrialized and automated through marketing automation.
For today's empowered consumers for whom marketers have found themselves a new mission: social listening.
“At its best, marketing automation is a combination of software and strategy. It should allow you to nurture prospects with highly personalized, useful content that helps convert prospects to delighted customers.” - Hubspot.
In this project, i identified first key steps of a marketing automation strategy and conducted a customer purchasing behavior analysis for a retail chain who have five segments of products who don't have reconciliation for customer data.
1. Define and prioritize objectives
2. Assess existing assets : Relationship strategy; Tech ecosystem; Data
3. Mapping the customer journey: it's important to map every possible digital or physical touch points that we could have with customers.
4. Understanding customers: analyze the existing customer database. Split customers into segments: demographic geographic behavioral
or based on customer journey. And start by segmenting on identifiable variables. After that a waterfall report to shrink down each segment by adding on different thresholds on each of the identifiable variables to find the population to start :
The list of key objectives of your marketing relationship strategy.
One program of communication for each key objective.
Scenarios & campaigns
A bunch of automation scenarios and campaigns in each program.