For the retail in Colombia, 2016 was a year in which household consumption and GDP growth were below the levels expected by market analysts. Honey is the flagship store of an apparel brand called FLOWER CO, in 2016 the brand experienced a decrease in sales and wanted to know whether there was a problem in the product mix or the location of the store.
In addition, they thought that beyond the overall slowdown of the economy, there could be other factors affecting their brand.
These were some of the questions they had:
- Could there be a gap between what the marketing team thought of their products/clients and how the message was coming across the consumers?
- Were the marketing campaigns being effective beyond the online channels?
- Was the brand truly embracing the omnichannel offer it has promised their clients?
- Were the market segments the brand had established as its niche market responsive to current ads and offers?
- Did they have enough information about their clients?
- Was there a problem with the sales force?
- Were they not properly motivated?
Retail in Colombia Common Problems?
- FLOWER CO did not know the traffic at the Honey location, thus they were unsure of the general traffic at the mall, let alone the number of people who went in front of the store, and even less the number of people who did go inside the store.
- FLOWER CO did not have a CRM system tied to the POS, thus they did not capture personal data about their clients, POS was connected to inventory system, they could know which references were popular but were blind to see who bought them.
- Basically, FLOWER CO had to answer two main questions, how many people and when do they visit Honey? Who visits Honey? Who buys at Honey?
To know the in-store traffic at Honey, a traffic measurement camera was installed, with this action we started to gather data to answer FLOWER CO´s first question.
Also, with a camera able to recognize demographics (gender and age) we were able to answer the second question. For the third question, bearing in mind the limitations of the POS of the client, we crossed available public records and the data they capture to find trends.
All this information is available in the cloud and can be downloaded and merged with business intelligence databases used by FLOWER CO. User profiles can be created by the system administrator, he can control who sees what kind of information. The SaaS is linked to the POS
Deployment of the SaaS in every store FLOWER CO has in large cities and provided to franchisees so they can also benefit from the data and its insights.
Full roll out, from project to a part of the daily operations of business, so it becomes an everyday source of data that is actionable for it retail operation in Colombia
It now becomes a part of the continuous improvement of FLOWER CO´s processes across areas like marketing, product development, customer journey and store designers…
Phase 1.A Data capture
Be able to understand the customer journey and identify who they are will allow FLOWER CO to optimize its marketing spending and other operational aspects. Meanwhile this information is also an insight to those in product design.
Phase 1.B Big Data and data visualization outcomes
1.B.1 Who enters the shop?
1.B.2 Who buys?
PHASE 2.Big data and data analysis
To think about the retail in Colombia
The CMO wonders whether this is the right time to invest, he thinks it should be fine to start with 25 stores, but the investment is 100K, how can he sell the project to the board in financial, commercial and marketing terms?
What will be the ROI of the investment?
How will the data impact other areas of the business, besides commercial and marketing, could you map the information flow?
Would you go on with the project?