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Tracy HermansDigital Marketing Manager l Wet Seal, LLC
PRESENTING
TODAY
What does it mean to be data driven?
SINGLE CUSTOMER VIEW
STRATEGY:
CREATE A SINGLE CUSTOMER VIEW CREATE A SINGLE CUSTOMER VIEW CREATE A SINGLE CUSTOMER VIEW CREATE A SINGLE CUSTOMER VIEW
OPTIMIZE
COLLECT RELEVANT DATA POINTSCOLLECT RELEVANT DATA POINTSCOLLECT RELEVANT DATA POINTSCOLLECT RELEVANT DATA POINTS
ANALYTICS:
DISCOVERY THRU DATA MODELSDISCOVERY THRU DATA MODELSDISCOVERY THRU DATA MODELSDISCOVERY THRU DATA MODELS
INSIGHTS:
MAKE MAKE MAKE MAKE DATA DRIVEN DATA DRIVEN DATA DRIVEN DATA DRIVEN DECISIONSDECISIONSDECISIONSDECISIONS
11111111
22222222
33333333
44444444
UNDERSTANDING THE CUSTOMER
“
”Source(s):Experian 2011, Single Customer View
WHAT ARE YOUR BUYER PERSONAS- CHARACTERISTICS
- PAIN POINTS
- MOTIVATIONS
- LIFESTYLE
- LOCATION
HOW DO THEY ALIGN WITH MARKETING GOALS?
WETSEAL | CASE STUDY CASE STUDY CASE STUDY CASE STUDY ---- QUALITATIVEQUALITATIVEQUALITATIVEQUALITATIVE
All of your work has a tactical
end game: to identify goal
centered customer strategies.
How to reach them, via
what channel, frequency of
messaging, types of content,
sales funnel systems and back
end lead capture systems.
Don’t fall in love with the data:
move to tactical marketing
for testing.
- Linked Media Group
“
Source: “How to Create a Brand Persona to Drive Marketing” Linked Media Group, 2015
”
BRAND PERSONA
AGE RANGE: ________________AGE RANGE: ________________AGE RANGE: ________________AGE RANGE: ________________
SELFSELFSELFSELF----DESCRIBED STYLE: ______DESCRIBED STYLE: ______DESCRIBED STYLE: ______DESCRIBED STYLE: ______
BUDGET: ___________________BUDGET: ___________________BUDGET: ___________________BUDGET: ___________________
||||JOB JOB JOB JOB ||||SCHOOL SCHOOL SCHOOL SCHOOL ||||OTHER OTHER OTHER OTHER
OTHER BRANDS: _____________OTHER BRANDS: _____________OTHER BRANDS: _____________OTHER BRANDS: _____________
PATHPATHPATHPATH----TOTOTOTO----PURCHASE: __________PURCHASE: __________PURCHASE: __________PURCHASE: __________
____________________________________________________________________________________________________________
____________________________________________________________________________________________________________
CASE STUDY | OPTIMIZEOPTIMIZEOPTIMIZEOPTIMIZE
DATA SOURCESDATA SOURCESDATA SOURCESDATA SOURCES W E T S E A L W E T S E A L W E T S E A L W E T S E A L
POS DATA (in-store, ecommerce)
MERCHANDISE FILE ((((historic, current)
ECONOMICS (census, indices)
SMS(zip code clustering)
STORE PROFILES
CASE STUDY | ANALYSIS + DISCOVERY ANALYSIS + DISCOVERY ANALYSIS + DISCOVERY ANALYSIS + DISCOVERY
ECOMMERCE DATA ANALYSISECOMMERCE DATA ANALYSISECOMMERCE DATA ANALYSISECOMMERCE DATA ANALYSIS
I N P U T S I N P U T S I N P U T S I N P U T S
Hypothesis:+ Demographic
+ Economic + Consumer
D A T A M O D E LD A T A M O D E LD A T A M O D E LD A T A M O D E L
Store Clustering:Mapped Users < 25 miles
spectral clustering
Validation: Correlation matrix
Cluster Bin PredictionMultinomial regression
R E S U L T SR E S U L T SR E S U L T SR E S U L T S
DiscoveryOriginally, we built a
statistical model to better predict assortment
(FF/Basics). What we found is that lifestyle was
secondary to demographic indicators, meaning what
drove FF was mainly economical.
CASE STUDY | VALIDATIONVALIDATIONVALIDATIONVALIDATION
ADDITIONAL SOURCESADDITIONAL SOURCESADDITIONAL SOURCESADDITIONAL SOURCES P I P E R J A F P I P E R J A F P I P E R J A F P I P E R J A F FFFF R E YR E YR E YR E Y
Teens directly command $75B of discretionary spending
• 2008 recession was their first formative economic experience
• Teens became budget conscious, value seekers; exhibited brand selectivity
• Wallet share shift from possession based expressions to share worthy experiences
TEEN DISCRETIONARY SPENDING HAS SHIFTED
CASE STUDY | EVIDENCEEVIDENCEEVIDENCEEVIDENCE
ADDITIONAL SOURCESADDITIONAL SOURCESADDITIONAL SOURCESADDITIONAL SOURCES I R I S M O B I L E I R I S M O B I L E I R I S M O B I L E I R I S M O B I L E
We analyzed SMS campaigns throughout 2014 and found that collectively:
• 39% of opted-in users did not have data enabled handsets that would allow for direct online purchase which further supports that today’s overriding issues for our demographic are economically driven
CASE STUDY | DATA DRIVEN DECISIONSDATA DRIVEN DECISIONSDATA DRIVEN DECISIONSDATA DRIVEN DECISIONS
Initially, we sought predictors of fashion to support our hypothetical assessment of our brand persona. Instead, we combined all data points and the data unfolded a different story. The data revealed ways that we as marketers could better spend and achieve a more efficient ROI, and build a better LTV model:
• SMS: Data Enabled Segmentation and Offers (Data Plans, Location Pings)• Email: Post-Purchase Offers to Store (Zip Code)
SUMMARY FINDINGS
BEGIN WITH AN
INITIAL HYPOTHESIS
ADD ALL DATA POINTS + BE READY
FOR REVEALING INSIGHTS
INTEGRATE INSIGHTS INTO THE INTEGRATE INSIGHTS INTO THE INTEGRATE INSIGHTS INTO THE INTEGRATE INSIGHTS INTO THE
CUSTOMER PATH TO PURCHASECUSTOMER PATH TO PURCHASECUSTOMER PATH TO PURCHASECUSTOMER PATH TO PURCHASE
T R A C Y H E R M A N S
Digital Marketing Manager, Wet Seal LLC
[email protected] | www.wetseal.com
Wet Seal is a pioneer in fast fashion retailing, sells apparel, footwear and accessories designed for young women of all sizes through retail stores nationwide, as well as an e-commerce website www.wetseal.com.
FOLLOW US
@wetseal instagram/wetseal
@tracysurfs instagram/tracyhermans
