how best-in-class sales leaders create better forecasts and increase revenue
DESCRIPTION
Let’s face it, a new or improved CRM won’t help most enterprises forecast more accurately, or even close more deals. Today, maximizing sales requires both art and science, and this need is driving a need for consumer friendly production analytics across the Sales organization in conjunction with serving the data starved Sales Operations function. Join Aberdeen's Sales Effectiveness Analyst Peter Ostrow in this free webinar and learn how the most progressive companies are creating better forecasts and more predictable revenue. Register today and learn: The pressures facing sales leaders related to forecasting The actions taken to improve sales forecasting with data analytics The capabilities and technologies used by Best-in-Class companies to leverage data How to improve your own sales forecasts through analyticsTRANSCRIPT
HOW BEST-IN-CLASS SALES LEADERS CREATE BETTER
FORECASTS AND INCREASE REVENUE
July 17, 2014
Enterprise-caliber Cloud BI
2
FEATURED SPEAKERS
Peter OstrowVP and Research Group Director; Customer Management, Sales EffectivenessAberdeen
Farnaz ErfanDirector, Product StrategyBirst
3
WEBINAR NOTES
Please send questionsusing the online interface
Attendees muted upon entry
4
AGENDA
• How Best-in-Class Sales Leaders Use Analytics to Turn Better Forecasts into Increased Revenue
• Why Birst for Sales Analytics?
• Q & A
CHASING THE CRYSTAL BALL
How Best-in-Class Sales Leaders Use Analytics to Turn Better
Forecasts into Increased Revenue
6
Takeaways
Sales effectiveness requires more than rip-and-replace
Willie Nelson was right all along
Learn from your cookies
Would a Vulcan make a good B2B salesperson?
Don’t forget the ketchup
7
Why we are here today
8
Why we are here today
9
What's keeping usawake at night?
10
What's keeping usawake at night?
11
Too often, the sales problemis a forecasting problem
12
Too often, the sales problemis a forecasting problem
44%
36% 35% 34%
23%
15%
0%
10%
20%
30%
40%
50%
Insufficientdata on
current dealsin the pipe
enteredby reps
Over-confidence,
“sand-bagging”
Lack ofmanager
enforcementof rep
data entry
Lack ofreps'
accountability
Inability tounderstandprobability
deals toclose
Inability toweight dealsby historicalperformance
Perc
enta
ge o
f res
pond
ents
n = 144
All companies
13
Too often, the sales problemis a forecasting problem
14
Too often, the sales problemis a forecasting problem
15
Can't we fix the forecast withbetter CRM adoption?
16
Can't we fix the forecast withbetter CRM adoption?
17
This is notsales enablement
18
CPQ
eSignature
Intelligence
Social
MobilePortals
Analytics
SPM
Gamification
Enablement
CRM cannot stand alone
19
Enter the data scientists
20
Best-in-Class Performance:Where do You Fit?
Definition of Maturity Class
Mean Class Performance
Best-in-Class: Top 20%
of aggregate performance scorers
94% of customer retention rate 13.2% year-over-year growth in average net client
value; 75% showed improvement 11.6% year-over-year improvement in team
attainment of sales quota; 69% showed improvement
Industry Average: Middle 50% of aggregate
performance scorers
81% of customer retention rate 1.0% year-over-year growth in average net client
value; 23% showed improvement 0.3% year-over-year improvement in team
attainment of sales quota; 26% showed improvement
Laggard: Bottom 30% of aggregate
performance scorers
19% of customer retention rate 1.9 % year-over-year decrease in average net
client value; 8% showed improvement 0.7% year-over-year decrease in team attainment
of sales quota; 20% showed improvement
BlankblankBlankblankBlankblank
21
Early adoption = smarter selling
88%
61%
41%
22%
77%
59%
38%
14%10%
30%
50%
70%
90%
Customerretention
Repsachieving
quota
Leadacceptance
rate
Leadconversion
rate
Perc
enta
ge o
f Att
ainm
ent
n = 261
Data analytics applied to deal velocity All others
22
Aren't these tools just for geeked-out managers?
64%
56%
48%47%52%
38%
30%
40%
50%
60%
70%
Employees with need,desire for analyticalfunctionality, with
access to BI
Employees usinganalytics in a self-
service capacity
Users engaged withanalytical tools ona weekly or more
frequent basis
Perc
enta
ge o
f Res
pond
ents
n = 83
Leaders Followers
23
…Not if you can achieve results like these
60% 60%56%
44%
38%
47%
30%
40%
50%
60%
Speed ofdecision-making
Trust inunderlying
data
Reduction inresponse time
to customerrequests / inquiries
Perc
enta
ge i
ndic
atin
g 4/
5 on
1-5
sc
ale
n = 83
Leaders Followers
24
How does this stuff work?
25
How does this stuff work?
26
How does this stuff work?
27
What should I be doing?
28
Does forecasting accuracy matter?
47%
59%
74%
85%93%
43%52%
58%
71%
82%
38%
51%55%
67%70%
25%
40%
55%
70%
85%
100%
180 days 90 days 60 days 30 days Immediatelyprior
Accu
racy
of S
ales
For
ecas
t
n = 139
Best-in-Class Industry Average Laggard
29
What benefits will a moreaccurate forecast accrue?
61% 61%
45%
33%
46%42%
33%28%
45%
25%22% 21%
10%
20%
30%
40%
50%
60%
70%
Using forecastingprocess
to add extra resourcesto deals most likely
to close
Understanding whichopportunities are most/
least likely to close
Using forecasting process
to “walk away” from deals
least likely to close
Using forecastingprocess to identify
potential “nodecisions”
Perc
ent i
ndic
atin
g 4/
5 on
a 1
-5 s
cale
n = 139
Best-in-Class Industry Average Laggard
30
What benefits will a moreaccurate forecast accrue?
83% 78%
55%50%
59%
40%32%
25%
10%
30%
50%
70%
90%
Understandingcustomers'
businesschallenges
Retaining topsales talent
Sales forecastperceived as
accurate/trustworthy
by sr. management,entire company
Sales leaders useforecasting process
to coach reps
Perc
ent i
ndic
atin
g 4/
5 on
a 1
-5
scal
e
n = 139
Best-in-Class All others
31
What should I be doing?
39%
56%
6%
17%
60%
22%
0%
15%
30%
45%
60%
On-demand, alwaysavailable in real-time;
no need to actually“publish” a forecast
Daily tomonthly
Quarterlyor less often
Perc
enta
ge o
f Res
pond
ents
n = 139
Best-in-Class All others
32
Never forget who's in charge
33
What's in YOUR pipeline?
13%
38%31%
7%
22%
36%
0%
10%
20%
30%
40%
50%
We are a dominant providerin our market and have
achieved full penetration ofalmost all our accounts
We have very strongpenetration
in most of our accounts butcould still benefit from
additional up-sell or cross-sellrevenue
We have reasonable accountpenetration but are definitely“leaving money on the table”
Perc
enta
ge o
f Res
pond
ents
n = 104
Best-in-Class All Others
34
Don't be that guy.
35
Don't be that guy.
36
What about mobility?
37
Are we consumingor creating?
180
22%27%
8%14%
24%28%
34%
17%
9% 7%
30%
50%
11%6%
0%0%
10%
20%
30%
40%
50%
Remote salesactivity=content
consumption, i.e.seeing but rarely/never changing/
entering data
Occasionally manipulatesdata on prospects/
customers/proposalsremotely, mostlywaits for full lap/
desktop to change/enter data
Remote sellersequally “see”and “do” on
remotedevices
Frequently manipulatesdata on prospects/
customers/proposalsremotely, still
reserves activityfor office/home
Location/device isirrelevant; reps canperform virtuall/all
work via tabletor smartphone
Perc
enta
ge o
f Res
pond
ents
n = 246
Best-in-Class Industry Average Laggard
38
Takeaways
Sales effectiveness requires more than rip-and-replace
Willie Nelson was right all along
Learn from your cookies
Would a Vulcan make a good B2B salesperson?
Don’t forget the ketchup
THANK YOU
For more information on this and other topics, please visit aberdeen.com
https://twitter.com/#!/peterostrow
http://www.linkedin.com/in/ostrowpeter/
WHY BIRST FORSALES ANALYTICS?
Enterprise-caliber Cloud BI
41
ADVANCED ANALYTICS FOR BEST-IN-CLASS SALES LEADERS
• Pipeline Growth & Velocity
• Sales Performance & Win Rates
• Sales Forecasting & Predictions– E.g. Likelihood of deals that would close
• Exception Alerts– E.g. Deals that exceeded benchmarks for
x many days
– Missed step in the sales process
– A stage 5 deal that is missing a contract
– Opportunities without NDAs
42
IN-APP EXPERIENCE, EMBEDDING ANALYTICS INSIDE SALESFORCE
• Higher adoption
• Better user experience
43
ACCESS TO ANY INFORMATION, FOR ALL USERS• Complete view of customer
– Data from ….
– E.g. Leads generated from social media vs. sales-outbound
• Analytics on mobile for traveling sales reps
• All users, one data!
– Others who are not Salesforce users
– E.g. Members of Finance, Operations, Support, Partners, etc. without a SFDC user license
& more…
44
Data Sources
BUILD A DATA-DRIVEN SALES ORGANIZATION
Challenges
– Outlook: forecast, quota, actual, predicated performance on 800+ sales reps
– Sales and product combined reporting and analytics
– Team performance on constantly changing territories
Results
– Sales performance ranking of reps, teams and regions on monthly, quarterly, and yearly basis – not possible within Salesforce
– 800 sales professionals | 1 forecast
– Sales management: saved ½ day a week
– TTV: 83 days
Why Birst?
– Multi-source analysis across Salesforce (sales data), SQL Server and Cognos TM1 (product data)
– Automatic detection of changing dimensions such as changing territories
– Pixel-perfect reporting with security rules already defined in Salesforce
“Earlier at D&B, we tried to build exec-level dashboards and we never achieved this success.”
Ted Mastalski
Leader of Global Solutions
45
Data Sources
WIN CUSTOMERS BY PERSONALIZING PRODUCT RECOMMENDATION
Challenges
– Identifying growth opportunities with existing clients
– Empowering advisors to manage their businesses effectively
– Large volumes of historic data, but no insight
Results
– Predictive analytics to identify hidden opportunities. E.g. client with $2M in assets and no retirement plan
– 2500 financial advisors using Birst make data-driven product recommendations to sell the right products to the right clients
– Brokers with Birst gathered 2X more assets than other brokers
Why Birst?
– Speed of Deployment
– Ease of use
– Scalability
Commission DataBack Office
Operational Data
“Advisors using the tool are bringing in new assets at twice the rate of those who are not using it.”
Catie Tobin
Head of Business Development
46
Data Sources
MASTER LEAD-TO-CASH TO DRIVE PROFITABILITY
Challenges
– Drive profitability by converting leads / trials faster
– Increase sales rep productivity
– Get faster insights to pipeline than manual reporting
Results
– Real time pipeline analysis – understanding usage, frequency and completed activities of trial accounts
– Reduce sales cycles
– Increase deal close rate
Why Birst?
– To go live quickly with a cloud deployment
– Self-service dashboards & mobile access
– Lead-to-cash across Marketo, Salesforce & Netsuite
– Customer-focused culture of Birst
“When we looked at the ease with which various BI solutions allow business users to construct, maintain, and add new sources to a data model, Birst blew everything else out of the water.”
Monique Herman
VP Business Operations
(Future)
47
Data Sources
IDENTIFY TOP SALES MANAGERS TO RAPIDLY GROW A BUSINESS
Challenges
– Grow sales org rapidly by identifying top performing sales managers who can train new reps
– Understand customer lifetime value to determine where to focus marketing and sales efforts
– Quickly resolve pipeline bottlenecks
Results
– Analysis of best market segments & customers who would buy multiple time vs. once
– Pipeline analysis to understand whether bottlenecks are customer, product, rep or region related
– Revenue growth: 83%
– TTV: 39 days
Why Birst?
– Salesforce solution accelerator
– Analytic snapshots on Salesforce
“For about the same amount of time we were idle with the previous analytic tool, we found ourselves actually up and running with Birst”
Lori BushPresident & CEO
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Q&A
49
LEARN MORE
• Download 2014 WOC Report
– Birst.com/wisdom2014
• Join us for a Live Demo
– Every Tues and Thurs @ 11:00 am PT/2:00 pm ET
– birst.com/livedemo
• Contact us
– (866) 940-1496 (or +1 415-766-4800)
50
THANKS