In conversation with Prisila, correspondent, Asia Business Outlook Magazine. Charoenporn shares her views on statistical techniques or models used to analyze and interpret customer data for segmentation purposes.
1. How do you approach market research and analytics to gather insights and drive data-based decision-making for international marketing initiatives?
Market research answers “why” while analytics tells you “what happens and what will happen”. Both market research and analytics cannot be utilized well without having the right business questions at the starting point. My holistic market strategy leveraging market research and customer insights is usually composed of these steps as follows:
I have used this common process in 15 markets across continents of Northern Europe, Eastern Europe, South Asia, and Southeast Asia to drive the whole marketing team's decision-making process. Indeed, it’s very effective and I can compare performances of different markets with this single approach. The set of questions was standardized while some questions were customized to tailor with each local market.
2. How have you customized market strategies that cater to the unique needs and preferences of different countries and cultures?
Using the right Market research methodology together with leveraging the local marketing expert/local domain industry expert can cater to differences. The set of standardized questionnaires shall be composed of demographics, behavior and psychographic values. In Asian countries, demographics play a significant role in segmentation while psychographic values matter more in Northern European countries.
"Implementing new approaches is never a challenge as long as they are still able to answer key business questions"
3. What statistical techniques or models have you used to analyze and interpret customer data for segmentation purposes?
I have used various techniques such as K Means, Multinomial Logistics Regressions and Latent Class Analysis to explore and compare results . However, the most convenient approach for me is Multinomial logistic regression because it’s easy to explain the result to business teams.
4. How do you stay updated on the latest statistical techniques and methodologies in the field of marketing analytics? Can you provide examples of how you have implemented new approaches in your work?
I have participated in multiple online community groups that bring in data scientists, researchers, data analysts together. Lots of findings, use cases, and techniques are discussed and exchanged.
Using the right Market research methodology together with leveraging the local marketing expert/local domain industry expert can cater those differences
Implementing new approaches is never a challenge as long as they are still able to answer key business questions. What matters is if those new approaches are accurate and precise and most importantly easily explainable to business people.
5. How do you ensure consistent branding and communication across different digital campaigns while catering to specific target audiences and campaign objectives?
I have the holistic go-to-market framework (one version that is distributed and shared among marketing team, CMO, CEO) which is composed of:
On a bi-weekly basis, the marketing (product and segment) team will update campaign schedules regularly to align with brand and mar-com teams to ensure newly launched campaigns (both strategically and tactically) are consistently and holistically communicated.