How to use your data to grow your online store

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2 How to use your data to grow your online store

3 Carolyn Harrington Co-Founder & CEO

4 Relax I am a professional! CEO of Moco Insight Magento Technology Partner Using data is create and grow businesses for over 10 years I love data and what you can do with it

5 What you will walk away with What data points you need to focus on Data is all about combining it - silos are bad! How to apply the above

6 Old school still has it s place

7 We are always on

8 Boom! Cyber Monday sales grew by 29% - $2.3 billion In two hours Alibaba generated $2 billion USD in sales and took a total of $9 billion USD Spending per year predicted to reach $2.357 trillion USD The roads are paved with gold right

9 Streets aren t paved with gold Competitors = cost per click is going up Everyone is sending your customer s The power has switched over to the consumer: so much choice products so cheap ability to shop 24/7 Scatter gun/generic marketing = limited impact

10 Winning ingredient

11 Why is data the winning ingredient?

12 The corner store

13 Bring back old school They knew their customers: what they purchased, had lapsed, price point, brands, size They knew their products: what colour/size etc sells, profit margins, performing stock, products for customers What campaigns were working: What to advertise, when and where All this produces higher repeat customers & profit margins!

14 Need to focus on the right things

15 Data, data everywhere E-Commerce creates a multitude of data: Google Analytics system Magento (product, transaction & customer) Social media Google Adwords

16 What we see. Businesses rely on three sources: Google Analytics system Total orders (Magento) There is a whole other world of data you are missing!

17 Data to put in your marketing tool kit

18 Website data points UTM source UTM term UTM content UTM medium UTM campaign Keyword search Exit page Referral source Regions Products Gender Profit Conversions Categories Total sold Customers acquired Customer lifetime value

19 Data for customer segmentation Customer lifetime value (profit) Average order value Weeks since last purchased Days between purchased Products recently viewed Number of purchase days Discount history Product attributes (size, colour, type, manufacturer) Customer attributes (gender, location, age) RFM (Receny, Frequency & Monetary value)

20 Product data points Manufacturer Region (state, country, etc) Attributes (style, colour, brand, etc) Volumes sold Revenue Category PROFIT Customer attributes (age, gender, etc) Cover units Marketing channel and campaign Conversion rates

21 USE THE COST FIELD!!!

22 PROFIT & PROFIT MARGIN

23 Data likes team work

24 Scenario Generic s don t work Your customer shop by attribute and aren t interested in all your SKUs Segment your customers by product attributes (type, colour, manufacturer, brand, size etc) Also by customer attributes (age/gender/region) Create campaigns using this information not one for all!!!!

25 Scenario New customer sign up Use data point number purchase days to identify how many purchased (74%) Use utm_campaign and utm_source to identify where top 20% customer came from Included country/state column to establish where they are located Identify best selling products for this group Create advertising campaign using the above data

26 Scenario Activate the first purchase Most used coupon and segment by gender/age/region Identify best selling products by age/gender/region/profit/profit margin/stock level Create templates based on data points information above Test the results

27 Scenario VIP customer Calculate most valuable customer using their RFM (recency, frequency & monetary value) Note shouldn t be based purely on value We put give score out of 100 VIPs have an RFM score of 75+ DON T include in a blanket , DON T spam Send s with coupons/products they are most likely to buy

28 Scenario Lapsed customers More accurate for customer who have purchased 2 times or more What price point do they purchase at How long since they last purchased Use a predicted next purchase if you can See on average a customer reengagement of 15%

29 A the winner is. Conversion rates are interesting but are deceptive over time You need to look at the bigger picture Are you happy with your marketing campaign ROI over time

30 Profit speaks louder than volume Volume is great but it doesn t keep the doors open Need to focus on profit, profit margin and stock levels. Profit allows you to keep the doors open, increase marketing budget and pay the staff

31 Secret to data Its about understanding ALL the data points you need to combine and use to build a profitable online store. You won t find them all in Google Analytics!

32 Carolyn Harrington Co-Founder & CEO mocoinsight.com