E-commerce is growing rapidly in last 5 years enabling 250,000 SMEs retailers selling online across e-commerce platforms. Yet they are facing tons of challenges in managing, sustaining, and scaling up their businesses due to lack of fundamental knowledge, capability, and tools which mostly can be solved with power of data and automation technologies. With over 10 years of experience in data & analytics combined with 4 years working in top e-commerce pioneers across SEA, Nam will share best practices of using Data Analysis and Artificial Intelligence to empower SMEs thrive in e-commerce to tackle these challenges.

1. 1
Using Data Analysis and Artificial Intelligence to
empower SMEs to thrive in e-commerce.
Bui Hai Nam
Chief Executive Officer
Datamart Solutions Pte. Ltd.

2. 2
• MSME Retailers on E-
commerce &
• 3 typical performance
marketing pitfalls &
• Best practices using data & AI
to tackle these challenges
Using Data Analysis &
Artificial Intelligence to
empower SMEs to
thrive in e-commerce.

3. Vietnamese E-commerce Economy is booming,
CAGR at 30% till 2025
3
3,079
2015 2018 2019 2020 2021 2025
Market Size (mil $) 8,040
5,024
480 300k+ online retailers
3.2% retail shares
38 mil online shoppers

4. Mostly driven by MSME businesses
MSME
Retailers
Big brands/
Retailers
By platform By seller size

5. E-Commerce MSME Retailers - Who are they?
1
owner with 4-5 staffs
1-2
Online channels
$10k-200k
revenue per month
2-3%
for marketing
(FB, GG, LZD,…)

6. • Product Selection
• Stock Management
• Competitive Management
• Performance Management
• A/B Testing
They run performance marketing based on
guess works
6

7. #1 Traffic is usually driven to their best-selling
7
Best-Selling
Products
“Better” Selling
Products

8. And the conversion rate lever is forgotten
8
Traffic x Conversion Rate = Orders
Effective ROI lever to pull

9. A simple conversion rate analysis can take the
guess work away
9
2% 3% 2.5%
3% 7% 1%
3% 5% 2%
Product A Product B Product C
Low Traffic
Medium Traffic
High Traffic
The sweet spot

10. #2 stock management is one of the most
common issues
10
• Lost business opportunity
• Lost business continuity
• Overspent on OOS products

11. Smart AI can detect spikes, forecast sales, and
proactively alert shop owners
11
Human Machine

12. And recommend actions based on facts and
analyses to back it up
• Lack of stock! Only 11
units are in inventory that
could be sold in next 18
hours
• Add 86 products in
order to sell in next 2
weeks

13. #3 competitiveness is also usually forgotten
13
Traffic Conversion
1%
Majority of 99% people don’t
buy is looking for alternatives:
99%
Buy Don’t Buy
Different Product
Better Value
Same Product
Better Price

14. A price comparison table is super helpful but
not easy to make and maintain it
14
• Search for competitors across all e-
commerce websites
• Matching their products vs
competitors’
• Keep all competitor price updated
regularly
• Put all the data in one-place for easy
decision making

15. This is where automatic data collection
effectively monitors competitiveness
15
• Automatic monitoring of
competitor’s visibility, stock
level, and price changes
• Optimize competitiveness and
product conversion rate

16. AI will optimize the pricing automatically
16
• 2 inputs:
- Price range
- Difference from competitors
• Algorimic engine will
determine the most optimal
price, and the best timing to
reprice

17. And help them oversee the most important
products on a single view
17

18. About using Data & Analytics for Brands &
Agencies
18
BRANDS
• Monitor Competior
• Identify Right Product to
Promote
AGENCIES
• Monitor performance of campaigns
• Real-time optimization of
stock/pricing issues

19. How Data & Analytics empower MSME Retailers
19
• Market Intelligence
• Business Intelligence
• Recommendation
• Automation
CONCLUSION
• Manual Monitoring
• Lack of Insights
• Guess Works
• Tedious Tasks

20. Bui Hai Nam - Datamart.vn