demand generation using mobile and data to boost bricks and mortar sales (1)
TRANSCRIPT
ACER CONFIDENTIAL
Demand Generation: using mobile and data to boost bricks-and-mortar salesFrancesco FedericoFormer Global Digital Marketing Director
London, 6 July 2016
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Customer Journey: The Dream
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Customer Journey: The Reality
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• Non linear
• Happens in “micro moments” throughout the day
• Cross-device
We need to have individually-tailored marketing propositions for each prospect/customer. Rule-based marketing automation tools are not enough anymore.
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A Simple Start: Acer.com
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Analyze, Understand, Engage: Our Recipe to master the journey
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• AnalyzeTrack users’ behaviour on our owned digital properties and cross-reference it with second/third party data in order to recognize patterns: purchase intent;
• UnderstandCapture in depth each user’s needs and expectations, to picture her/his context;
• EngageAct in real time with personally tailored messages and offers: our best bet in fulfilling users’ needs.
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First Step: Implementing Real Time Intelligent Pricing on Acer.com properties
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It all starts with real time tracking on Acer.com
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All pages are grouped into macro sections
(Homepage, Laptops, Support, etc.)
Web visitors are mapped in real-time along their journey
Acer.com sections
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We then assign an Engagement Score to each user
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Each Acer.com visitor is assigned an Engagement Score based on which our
acquisition/retention strategy will adapt.
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Prospect Conversion: Dynamic acquisition
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Centered Example
Sidebar Example
Proactive behaviorally targeted messaging reflect the user’s top product interest and provides
immediate link to Online Retailers
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Prospect Conversion: Results
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This user is browsing many notebook and 2-in-1 pages, showing hot interest for our products.
By looking at the value of those products we could choose to propose an outbound call to
try finalize the sale, while for lesser value products we could just show a banner to our e-
commerce store.
In this way we commiserate marketing acquisition investment to the actual or
potential value of the customer.
Acquisition costs -20%Conversion rates +30%Key Variables Considered:
Product Value (margin and lifecycle)
Customer Value (actual or potential)
Previous Owned/Paid/Earned Media Interactions Location and Channel Partners Promotions
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Second Step: Data-powered creatives
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Informing the media mix with data
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Google AdWords RLSA rely 100% on a rules-based approach.
This results in either:
1. Excluding highly engaged prospects 2. Trying to guess which audience they should be in 3. Inundating them with irrelevant ads
(It also requires a lot of work to configure and keep track of the rules.)
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A 35% Clickthrough Uplift vs. Rule Based Retargeting
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We use our user scoring to bucket people into the right Remarketing Lists based on their overall interest categories
and real time engagement scores.
Model A
Model B
Model C
Model D
User receives the right Adwords creative
2015 Model B
We know what each user was most engaged with
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Third Step: Bridging the gap between online and offline
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Challenges
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• Data!Often sellout data is not given, thus it is very difficult to provide enough stores coverage = high risk of sending customers in stores with no product availability = customer lost to competition;
• Hard to align with local promoThe opportunity of aligning in real time with hyper-local in-store promotions is huge, but very hard to grasp due to data alignment issues and business decision lead time.
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The opportunity of granular analytics
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Along with complexity there is also the great
opportunity of matching media performance with
retail footfall.
By identifying demand/supply
unbalances media mix can be further geofenced
and segmented to achieve ultimate
efficiency.
Thank you
Let’s continue our conversation
@frandrake