Using big data to increase the bottom line for vacation rental management companies

1. Using Big Data to Increase the
Bottom Line
October 2013
For Vacation Rental Management Professionals
Amy Hinote ↔ aehinote@thenavisway.com ↔ 251-455-4994

2. Agenda
1. What is big data?
2. Impacts of big data on the technology development in
the vacation rental industry
3. Sources of data for professional property managers
4. Input vs. output
5. Step by step process for using vacation rental data to
impact revenue
6. How-to examples
1. Pricing
2. New customer acquisition
3. Customer retention
4. Homeowner retention/acquisition

3. What is Big Data?
• Big data is the collection of data
from traditional and digital
sources, inside and outside your
company, that represent a source
for ongoing discovery and
analysis.
• Big Data has come to the
forefront because of increased
ability to inexpensively store and
work with large datasets, both
unstructured and structured.

4. What is Big Data?
• Big data isn’t constrained to digital inputs (i.e. web
behavior, web app behavior, social networks.)
• In the vacation rental industry --we can’t exclude
traditional data derived from how your guests interact
at your properties, with your call center and at the point
of sale.
• As much as we talk about automating all
communications, there is a need for personal
interaction. If we limit our data input solely to digital
inputs, we can miss the big picture.

5. 5 V’s of Big Data
• Volume –the amount of data your collecting
• Velocity –the speed of information generated
• Variety –the kind of data available
• Veracity –the accuracy and validity of the data
• Value –what it means to you

6. What big data can show you
Once you start tackling big data,
• You’ll learn what you don’t know
• You’ll likely be proven wrong on some paradigms
you have held close
• You’ll be inspired to take steps to resolve any
problems.
• You can use the insights to improve your customer
engagement and homeowner acquisition strategies
• You will add more value to both your offline and
online interactions.

7. What is Big Data?
• Unstructured data: Information not organized or
easily interpreted by traditional databases or data
models.
• Multi-structured data: A variety of data formats and
types and can be derived from interactions between
people and systems (i.e. web data, online marketing
data, lead data in Narrowcast, data provided in
PMS, which includes a combination of text and visual
images along with more structured data like forms or
transactional information.

8. ISILink
FRS
Entech V12
PropertyPlus
Website
Distribution
Channels
Web App NAVIS
CRM

Payment
Processing
??? ???

9. 3rd
Party
ISILink PMS
Escapia Other PMS
Modules
Website
Distribution
Channels
Web App NWC
CRM

Payment
Processing
??? ???

10. What is Big Data?
Just as a note, as digital sources of data increase
—and as marketers enhance the customer
experience across devices, properties, face-to-face
interactions and social platforms—
multi-structured data will continue to evolve, especially
in the vacation rental space.

11. Data Sources for Property Managers
• Marketing Activity (online and offline)
• Lead Management System
• Call Center Information
• Website Activity/Analytics
• Property Management System
• Customer Behavior Before and During the Stay
• Face-to-Face Interaction
• Re-engagement Data
• Ancillary Spend
• CVB/DMO
• City/State/Regional
• Geo-Analytics

12. The good news…
What is finally coming down the pipeline in
technology is that you will be able to analyze –
and USE -your data from multiple data sources
to grow revenue.
You can start today.

13. The future in vacation rental data
to grow revenue
One-stop
data
marketing
system
Accurate
data
Inaccurate
data/
garbage
Ordered
garbage
Revenue-
generating
insight

14. The future in vacation rental data,
for example.
One-stop
data
marketing
systemCustomer
feedback
collected and
scored during
and after the stay
Only surveys
collected in
email after the
stay
Limited view
of customer
experience
Actionable
insighton ways
to improve the
customer
experience
Bad or incomplete data can lead to bad decisions, which is worse than no decision.

15. Using data to increase bottom line:
step by step
1. Determine Objective
2. Identify Metrics
3. Identify Data Input
Sources
4. Begin accumulating clean
data in systematic way
5. Examine Findings
6. Take Action

16. • Pricing
• Marketing
• Customer Retention
• Owner Acquisition
Using data to increase bottom line
step by step

17. 1. Determine objective.
I want to know if and when I should adjust rates on my 2
bedroom condos for Thanksgiving week.
2. Identify metrics.
1. Year-over-year comparisons
2. Booking window
3. ADR
4. Demand from non-booked data
5. Booking Pace
6. Call volume
Using data to increase bottom line
Pricing

18. 3. Identify Data Input Sources
1. Property Management System
2. Call center/Lead Management System/NWC
3. Face to face interaction (if you have walk-ins)
4. Web Analytics (Search)
4. Begin accumulating clean data.
1. Property types are segmented in your PMS
2. Create a way to collect property type information and accurate
reason for not booking on lead/not booked data.
3. Track walk-in requests as leads.
4. Add analytics on your website for availability requests and quick
search inquiries.
Using data to increase bottom line
Pricing

19. Findings (if you have accurate data)
Take Action: Raise rates.
Using data to increase bottom line
Pricing
Findings: Week 47
ADR ↑ 4%
Booking Pace ↑ 3%
Date of first not-booked inquiry October 18
Requests for 2 BRs with no availability: Website 88
Requests for 2 BRs with no availability: Call Center 14
Requests for 2 BRs with no availability: VRBO 5
Requests for 2 BRs with no availability: Walk-ins 1

20. 1. Determine objective.
Am I losing market share from any of my top feeder markets for
October?
2. Identify Metrics
1. Leads and Inquiries: City/State/Zip, year over year, and YTD
2. Guests: City/State/Zip, year over year, and YTD
3. Geo-targeted marketing efforts, year over year, and YTD
4. Web-traffic by geography, year over year, and YTD
Using data to increase bottom line
Marketing

21. 3. Identify Data Input Sources
1. Marketing Activity
2. Property Management System
3. Call center/Lead Management System
4. Web Analytics (Search)
4. Begin accumulating clean data.
1. Tracking marketing activity by type and location.
2. Make sure city/state/zip is collected on leads.
3. Make sure web analytics are set up correctly.
Using data to increase bottom line
Marketing

22. 5. Findings (with accurate data)
Take Action: Put together geo-targeted marketing effort.
Compare to area statistics from CVB/DMO
Using data to increase bottom line
Marketing
$0
$300,000
$600,000
$900,000
$1,200,000
$1,500,000
$1,800,000
2011 2012

23. 1. Determine objective.
Is my churn rate higher or lower than the previous year?
2. Identify Metrics
1. 2011 and 2012 stays by month (include guest data)
2. 2013 stays by month (include guest data)
Using data to increase bottom line
Customer Retention

24. 3. Identify Data Input Sources
1. Property Management System
4. Begin accumulating clean data.
1. Create a comprehensive system for connecting guest records in
the reservations department.
2. If you are using source codes, establish consistency.
Using data to increase bottom line
Customer Retention

25. 5. Findings
Using data to increase bottom line
Customer Retention
0%
20%
40%
60%
80%
100%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2011
2012
2013

26. 6. Take Action
April, May, August
and September have
trended downward
significantly.
1. Remarket to past guests in these months with targeted offer.
2. Aggregate and dedup the entire list and determine who stayed
with you in 2011/2012, who hasn’t been back or made a future
reservation and create a strategy for getting them back (may
include email marketing, lifecycle email messaging, or even
outbound phone calls or surveys)
Using data to increase bottom line
Customer Retention
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2011
2012
2013

27. 1. Determine objective.
Which property types had the most lost revenue based on
demand?
2. Decide what you want to measure.
1. Demand from not-booked data by property type, by
complex/community, by location
Using data to increase bottom line
Owner Acquisition/Retention

28. 4. Identify Data Input Sources
1. Property Management System
2. Call center/Lead Management System
3. Web Analytics (Search)
5. Begin accumulating clean data.
1. Property types are segmented in your PMS
2. Create a way to collect property type information and
accurate reason for not booking on lead/not booked data.
3. Track walk-in requests as leads.
4. Add analytics on your website for availability requests and
quick search inquiries.
Using data to increase bottom line
Owner Acquisition/Retention

29. 5. Findings
Using data to increase bottom line
Owner Acquisition
0
100
200
300
400
500
600
Call Center Web Searches
with No
availability
3rd Party
Inquiries
Walk-ins
1 BR Condos
2 BR Condos
3 BR Condos

30. 5. Findings
You can further segment by
complex and location.
6. Conclusion
Acquisition: Target these complexes or property types with
legitimate marketing campaigns with compelling stats
Retention: ―Show and tell‖ the levels of demand to your
homeowners
Using data to increase bottom line
Owner Acquisition
0
100
200
300
400
500
600
Call Center Web Searches
with No
availability
3rd Party Inquiries Walk-ins
1 BR Condos
2 BR Condos
3BR Condos

32. Using Big Data to Increase the
Bottom Line
October 2013
For Vacation Rental Management Professionals
Amy Hinote ↔ aehinote@thenavisway.com ↔ 251-455-4994