Utilize big data analytics to gather insights on user preferences, behavior, and browsing history. Leverage this information to provide personalized product recommendations, increasing the chances of conversion by offering relevant and tailored options.
Targeted Advertising: Big data analysis enables precise audience segmentation based on demographics, interests, and past purchase behavior. Use this data to deliver targeted advertisements that resonate with the specific needs and interests of individual users, leading to higher conversion rates.
A/B Testing and Optimization: Apply big data analytics to conduct A/B testing of various website elements such as layout, design, messaging, and call-to-action buttons. Analyze user behavior and conversion rates to identify the most effective configurations, optimizing your site for better conversion performance.
Customer Journey Analysis: Leverage big data to analyze the entire customer journey, from initial site visit to conversion. Identify potential bottlenecks or areas where users drop off, and implement targeted improvements to enhance the overall user experience and increase conversion rates.
Real-time Personalization: Utilize real-time big data analytics to dynamically personalize the website experience based on the user's current context, such as location, time, and device. By offering relevant content and offers in real-time, you can create a sense of urgency and increase the likelihood of immediate conversions.
Predictive Analytics: Utilize advanced predictive analytics algorithms on big data to forecast user behavior and anticipate their needs. By understanding user preferences and purchase patterns, you can proactively offer personalized incentives or recommendations, driving higher conversion rates.
Customer Segmentation and Customization: Utilize big data to segment your customer base into distinct groups based on various factors such as demographics, purchase history, and preferences. Tailor marketing messages and offers to each segment, increasing the relevance and effectiveness of your communications, and driving higher conversion rates.
Enhanced Customer Support: Utilize big data analytics to gather insights on customer interactions, feedback, and support tickets. Analyzing this data can help identify common pain points and address them proactively, leading to improved customer satisfaction and ultimately higher conversion rates.
By leveraging the power of big data analytics, you can gain valuable insights into customer behavior, personalize the user experience, optimize your site, and tailor marketing efforts. This data-driven approach can significantly increase your site's conversion rate and overall business success.
2. 7 Ways Big Data will increase Conversion Rate on your Site
3. Helps create a data
driven strategy
• Conversion of big data
into data driven
marketing strategies
• Effective in reaching
potential customers
thus increasing profit
margins and revenue
4. Allows you to understand your
customers
• Customers are aware and
educated
• Using big data, sales increases by
60%
• Customized service to the
consumers
• Thus, big data is an accurate way
to understand, attract, nurture and
guide your customers
5. • Informs you on how is the
product being perceived in
the market
• Access to customer reviews
• Reviews can be used as a
valuable insights, to improve
product
• Top-notch seller customers
are self-driven
Helps evaluate your product
6. Keeps your data up-to-date
• Big data tools such as CRM
keeps data organized and
secure
• A sales pipeline template will
give you clear idea on potential
leads and forecasting ideas for
strategies
7. Better Pricing Decisions
• Analyze the big data you have
on your customer to know the
exact prices and demands in
the market
8. Suggest Relevant Reccomendations
• Predict the next steps of your customer!
• The more relevant the recommendation, the higher
the rate of conversion
9. Increase Customer Responsiveness
• Customers tend to shop more on
websites with a responsive design
• With the lower level of patience in
customers the higher the
responsiveness of the website has a
higher conversion rate
Non- Responsive Responsive
10. FIVE OF THE SCARIEST PREDICTIONS ABOUT ARTIFICIAL
INTELLIGENCE
11. • Jobs are getting
automated
• Proponents of AI
consider new jobs
will be created
• AI will lead to next
world war III
• It’s not AI that’s
scary, it’s the
weapons
• Diagnosis will be
easier and earlier
• Industry will become
data driven
• Patient’s privacy will
be compromised
UNEMPLOYMENT WAR ROBO DOCTORS
12. • They have access to all your
moves and all your data using
facial recognition and AI
• Claims to reduce crimes
• Social credit systems
MASS SURVEILLANCE
• AI and facial recognition biases
based on color, race and gender
• IBM is tackling discrimination in AI,
by providing 2 data sets of various
skin tones and attributes
DISCRIMINATION
13.
14. DEEP LEARNING AI DIAGNOSED
ALZHEIMER’S 6-YEARS EARLIER
THAN CONVENTIONAL
METHODS
15. How do we do this ? By determining
metabolic changes
in the brain
OBJECTIVE: TO DIAGNOSE ALZHEIMER’S 6 YEARS EARLIER THAN CONVENTIONAL METHODS
17. Example of fluorine 18 fluorodeoxyglucose PET images
A. 76 year old man
with AD
B. 83 year old
woman with MCI
C. 80 year old man
with non-AD/MCI
Note: The researchers had access to 2100 FDG-PET images, from 1002 patients MCI: Mild Cognitive Impairments
19. Post training the algorithm, the
scientists tested it on a new set
of 40 imaging exams from 40
patients that it had never
studied.
20. The algorithm was able to score 100% at detecting the disease on an average of 6 years
earlier than the final diagnosis was made.
Editor's Notes
Do you know how much %of your sales you can increase by utilizing big data? 60% . Do you know how much of the big data is being processed, analyzed and utilized rightly? 0.5%
90% of the images were used for training the deep learning model, and 10% of the images were used to test the ability of the trained model to evaluate model’s ability to predict if the patient had Alzheimer's using patients brain image data. The trained model was able to predict the incidence
