Contextual personalization helps businesses deliver value to the customer based on real-time data.
Organizations
have long understood the need to establish an online presence. In the
last decade, e-commerce has grown immensely and according to eMarketer,
the global retail e-commerce sales are expected to reach USD 4 trillion
by 2020. As organizations fight for a larger share of the e-commerce
market, personalization has emerged as pivotal, especially as customers
get more savvy and demanding. Basic personalization such as using the
first name in the greeting is not enough for today’s always connected,
hard to engage, and easily distracted customers.
Up
until now, personalization involved using a blend of profile
information, historical data, data analysis, and digital technology to
understand user behavior and deliver individualized messages and
offerings to current or prospective customers. However, the wealth of
data that businesses are now amassing has given rise to a powerful new
tool – contextual or real-time personalization. According to the
Real-Time Marketing Insights Study, conducted by Adobe and Direct
Marketing Association (DMA), 77% of marketers surveyed believe real-time
personalization is crucial, and most are planning to implement
real-time technologies that can help improve personalization efforts
with more relevant data.
Personalized to the immediate context
Contextual
personalization uses a combination of historical and real-time data to
derive contextually relevant, real-time insights about customers. For
instance, businesses can map the customer journey on their past orders
to anticipate needs and provide customers with the information they are
really looking for while shopping.
Contextual
personalization helps businesses select and provide information that
will deliver value to the customer based on their current situation with
real-time data, including:
- Day and time
- Geographic locations
- Demographics
- Devices and browsers
- Loyalty statuses
- Email preferences
- Browsing history
- Customer history – recent transactions, interactions, and site visits
Personalized with chatbots
Recently,
Taco Bell unveiled its TacoBot within the Slack messaging platform that
allows busy workers to chat with a bot to order a Taco. Amazon too has
launched their bot ‘Alexa’ to interact with customers intuitively
through voice services. Such virtual robots or chatbots, powered by
artificial intelligence are set to change the way businesses engage with
customers. They will help bridge the gap of personalization that
customers face in online shopping.
Chatbots
will revamp and reinvent the way brands interact with their customers
making online shopping personal and interactive. In addition, chatbots
will be able to quickly understand the customer context, helping deliver
better customer service and amassing rich data on customer habits –
what they use their device to check and when, upcoming plans, and more.
This data would then help deliver relevant shopping experiences:
updates, information, and recommendations that would in turn, help
increase traffic and conversion rates.
Location-based commerce
With
location tracking, e-commerce businesses can gain deeper insights about
their users and provide an optimized customer experience with relevant
information, products, and services to fit their geographic needs. For
instance, businesses can provide relevant discounts, online reviews,
in-store navigation, latest trends, etc. when a customer is in the store
or near the store. This will help establish trust and credibility,
making it easier to eventually convert prospects into customers. Many
organizations such as Best Buy, Gap, and Victoria’s Secret are already
using location-based technology in their mobile advertising campaigns to
drive their in-store traffic.
Clearly, contextual personalization is the way forward.
As
contextual personalization moves in and shakes up the marketing world,
we at Skava, an Infosys company have designed Skava Commerce to enable
new, richer ways of engagement. Skava Commerce offers a native big data
product, user-based recommendations, and integrations with key
third-party vendors. These include insights and recommendations on
products that were bought together, global / category top sellers,
‘suggested for you’, similar products, ‘also viewed’, and much more. In
addition, it allows admin users to create a wealth of customer
segmentations based on spending levels, product categories,
demographics, geographic location, and other customized parameters. To
complete the picture, Skava offers detailed and rich analytics that help
leverage insights to offer tailored content, pricing, and promotions.
E-commerce Trend...
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