Showing posts with label demand generation implementation. Show all posts
Showing posts with label demand generation implementation. Show all posts

0 What Really Creates Marketing Automation Success: Data from Gleanster

Research firm Gleanster released its free “Gleansight” report on marketing automation late last month. I was principal author for much of the document and drafted the survey questions, although I didn’t write the individual vendor profiles or administer the survey. (I’ll also share in the revenues, which come when vendors pay for the names of people who download the report.) Although I’m obviously biased, I do think it’s an excellent product and highly recommend it.

Many readers of the report will be most interested in the vendor profiles and survey-based rankings. But I have my own data on those, so I’m more interested in the answers to the general survey questions. These asked why people implement marketing automation, what challenges they face, and what contributes to success. The survey compared answers from top-performing marketing automation users with answers from everyone else. This gives especially interesting insights (or should I say...GLEANSIGHTS) into the differences between sophisticated users and their less experienced brethren.

Here are some highlights – please look in the report itself for details.


Reasons to Implement: top performing companies listed higher revenue, better leads, and more leads as the most important reasons to use marketing automation. All other companies also listed revenue and more leads in their top three, but their most common answer was decreased marketing costs. By contrast, marketing efficiency ranked fourth among top performers and much lower among all others.

My interpretation is that top performers have learned that marketing automation might make you more efficient but won’t actually reduce your total marketing budget.  Other, less experienced companies that expect cost savings will probably be disappointed.  If anything, marketing automation will probably increase their marketing spend – hopefully with an even larger improvement in the revenues and leads to compensate.


Value Drivers: Both groups agreed that the two most important predictors of marketing automation success are cooperation with sales and ability to measure return on investment. But the top performers' third item was easy-to-use system while the others chose adequate staff training. This is a really interesting divergence.

The Gleanster people tell me that many of the top performers are now using their second marketing automation system because their first was too hard to use.  In other words, this is the voice of experience, and that voice is saying that training by itself can’t overcome a difficult system. Less-experienced companies who are relying so heavily on training may find it's not enough. But let’s not overstate this point: training is certainly necessary for success even if it’s not sufficient. Perhaps the top performers discounted training in part because they already had a lot of it.

Back to the data.  Both groups rated having an analytical culture as the fourth-most important value driver, while listing outside help, change management, and organizational resources as the least important.

These answers shed important light on the on-going debates about how marketers should approach their automation deployments. The message is clear: success depends on a marketing department’s own skill level, not on outside resources. A marketing department that pays attention to sales needs, carefully measures ROI, and makes fact-based decisions will succeed with marketing automation just as it probably succeeded without it.. A group that hasn’t mastered those basics won’t succeed at marketing automation no matter how much training, change management, and external assistance it brings to bear.


Challenges: Gleanster didn’t send me responses to this question broken out by top performers vs. all others. For the combined group, the top two challenges cited were data quality and creating content; the next three were poor marketing processes, lack of staff, and selecting metrics. These are all factors controlled by the marketing group. The lowest ranking factors were all the external ones: organizational culture, senior management mindset, lack of IT support, and lack of funding.

This is consistent with the previous answer: marketers create their own success. Marketing automation is just a tool.  It will help a well-run department work better but can’t save a poorly-run department from itself. Massive re-engineering isn't necessarily required to deploy marketing automation, but departments that lack a solid foundation need to build one before automation can do them any good.

0 The Easiest Way to Get Started with Marketing Automation? Answers in the Pictures.

Here’s more proof that the apocalypse is near: I’ve discovered the “remove background” feature in Powerpoint. This makes it even easier for me to doctor photographs for my presentations. The fabric of reality cannot long survive so much stress.

The immediate subject of my attentions is next Tuesday’s Webinar “Marketing Automation: One Step at a Time”, sponsored by Act-On Software.

The dominant image of this Webinar, and the eponymous white paper (available on the RaabGuide web site), is a high stone wall representing the effort required to deploy a marketing automation system. More specifically, the wall represents the effort of a traditional best-practice approach, which requires reviewing all marketing processes, designing new programs, creating new content, and working out alignment with sales. It’s a high wall indeed, and many companies just can’t climb it.



As I wrote in a post last December, several strategies have emerged to deal with this challenge. Now I’m delighted to be able to illustrate them.

Training: The wall is high but marketers can learn to jump higher. What they need is training in the pole vault.



Ease of use: Let’s lower the wall so marketing automation is easier. Apply a jackhammer to knock it down a few feet.


Incremental deployment: Break the deployment process into small, manageable stages. Let’s add a staircase with someone taking baby steps.



Service: Marketers should let specialists do the heavy lifting. The experts can carry them over the wall with a crane.



You’ll be pleased to know that the focus of the Webinar isn’t my new-found graphic capabilities. It’s how to succeed at incremental deployment, the strategy recommended by Act-On. Without giving too much away, the key is starting with the right tasks so you get some immediate benefit and build a foundation for future growth but don’t take on too much at once. Yes, I have some specific suggestions…but you’ll have to tune in to hear them.

0 Act-On Buys Marketbright Assets

Act-On Software announced last week that they had purchased the assets of Marketbright, a pioneering marketing automation vendor that has struggled in recent years. Marketbright’s problems have been obvious for months, so that they would vanish is not news. The interesting question is why Act-On made the purchase.

I discussed this last Thursday with Act-On CEO Raghu Raghavan. Part of his answer was because they could: having raised $10 million in June, Act-On can now consider acquisitions of less-well-endowed competitors. Beyond that, Raghavan cited several narrow benefits, including the chance of converting Marketbright customers to Act-On, the business knowledge and skills of key Marketbright employees, and some design features of the Marketbright system. He made clear that the actual Marketbright software will not be merged into Act-On because they are built with different technologies.

In other words, the Marketbright acquisition was a tactical measure to pick up some modest assets at a modest price. It is neither central to Act-On’s current strategy nor a shift towards a new strategy.

That strategy has remained remarkably consistent. It boils down to providing an easy transition between basic email systems and full-scale marketing automation. Raghavan said that Act-On has now deployed a consistent sales process to convince marketers they can benefit from replacing multiple point solutions with a single Act-On installation, even without the major process reengineering or staff training recommended by other marketing automation vendors.

This is clearly a successful argument: Act-On just added its 350th client, and is on pace to triple its total over the next twelve months. Most buyers are small businesses, and many are in financial services, insurance, retail, healthcare, and education rather than high-tech. Installations at large companies are often used by small groups who want an alternative to the existing corporate marketing automation system. The system’s $500 per month starting price and no-annual-contract policy encourage such casual implementations by reducing the financial risk.

In fact, the risk is so low that Act-On has actually reduced its free trial period from 30 days to 14 days and eschewed the freemium offers used by competitors Genius and LoopFuse. Raghavan argues that marketing automation systems are too complicated for freemiums to work well. (For what it’s worth, Genius and LoopFuse seem satisfied with their freemium results. Beyond inducing trial, freemiums can also attract long-term users who will move up to the paying version when their needs expand. Agencies who use freemium versions at small clients may also use the same product for larger clients who will pay for the system.)

If it sounds like my discussions with Act-On have centered more on strategy than product features, that’s correct. Raghavan argues marketing automation vendors' success is now determined less by product features than repeatable, profitable processes for sales, deployment, and support. He said Act-On has developed these processes and can now safely accelerate its growth with predictable results. One change the company plans is to expand its managed services, such as help with deploying campaigns. Some of these services will come from Act-On and others by agency partners.

Although Act-On sells the product as a replacement for existing point solutions, the company says clients do use additional features fairly quickly. The most popular are drip marketing, anonymous visitor identification, sales integration, and Web traffic analysis. Complex nurture campaigns and lead scoring are used much less. Under-utilization of advanced features is common across all marketing automation systems, but it may also reflect Act-On’s sales pitch that clients don't need extensive changes to their marketing processes. Similarly, it's tempting to argue that clients' demand for managed services reflects the company’s deploy-first, change-later approach, but that’s also something that clients of all vendors consistently request.

In short, Act-On is doing quite nicely by ignoring the industry conventional wisdom that process change and planning are necessary for marketing automation success. But that doesn’t mean the conventional wisdom is wrong. After all, Act-On’s main sales proposition isn't about marketing automation: it's about making existing tasks easier. It also helps that Act-On is selling to small, consumer-oriented firms, whose marketing automation needs are genuinely simpler than at larger, B2B marketers. In fact, although Act-On is selling to slightly larger companies than micro-business specialists Infusionsoft and OfficeAutoPilot, its resembles them in several ways.

The real test of Act-On comes after clients have gained experience with it and find they do need marketing automation training and process change. So long as Act-On has the features and services to support this – which I believe it does -- the clients should be happy and renew. But if they find they’ve outgrown Act-On because they need more change more than they originally realized, they’ll have to look elsewhere.

0 Eloqua Adds Free Implementation Offering

On Monday, Eloqua announced a new free deployment service for its clients. This is part of a larger industry trend to offer free deployment. It follows last month’s free deployment offer from Eloqua reseller Pedowitz Group, which generated quite a bit of comment on this blog. The new service, called QuickStart, will also be delivered by Eloqua partners, giving them an opportunity to start a relationship that could lead to future paid business. Crafty.

Eloqua Senior Vice President Paul Teshima, who is in charge of post-sales support, said the new program includes system configuration, CRM data integration, setting up an email template, landing page, three-touch lead nurturing program and a lead scoring discussion. It is delivered remotely and can be completed in two days to two weeks, depending on how much time the client has available. Advance preparation involves filling out a survey and receiving (if not reading) simple documentation. Clients fill out a workbook during the sessions and are the consultant leaves behind a 90 day plan for future action.

Teshima said the new program was developed in response to customer requests for a fast way to get some immediate use from their systems. It is a subset of the company’s year-old SmartStart program, which take five days or longer but includes more extensive email set-up; data posting from an external Web form; deeper CRM integration including lead flow, activity-triggered sales alerts, lead assignment, and email opt-outs; creation of either a lead scoring or lead nurturing program; and several types of marketing assessments and planning. SmartStart involves on-site consulting and costs $3,000 to $8,000.

The difference in scope between QuickStart and SmartStart provides a useful reminder of the importance of digging into the details of vendor claims about deployment. The question isn’t whether it’s free or can be done in one day, but what’s included and how much your company must do in advance.

The reality is that a complete demand generation program is something you develop and expand over time. A good start is important but it’s only a start.

Another reality is that most companies need help with improving their programs. Teshima pointed to Eloqua's customer success managers, who meet with each client quarterly to review system usage and develop a plan for improvements. They are compensated solely on retention rates, so their focus is on making better use of existing components rather than selling new licenses.

Eloqua also has its professional services group and consulting partners to provide more hands-on assistance. Other vendors also provide such services, either with their own own staff or through partners.

My point is to recognize that you’ll very likely want to purchase such services to get the most value from your demand generation investment. If that sounds like bad news, I guess you don’t absolutely need to. And while you’re saving money on that, you can also change your car’s oil and cut your own hair to save money on mechanics and stylists.

Sarcasm aside, a few companies already have skills to deploy a demand generation system effectively, but most do not. The reason you pay money for these systems is because they’ll help you do a better job. Not investing in the training and consulting means you’ll get less value than you should. Of course, you still need to invest wisely, in the sense of getting the right training and consulting. And, yes, you can probably get some value even without outside help.

Training and consulting are ultimately business decisions about where you can spend money to get the greatest return on your investment. A small investment in using your system effectively is likely to be a wise choice.

0 Demand Generation Implementation Survey: Half of Users Deploy Basic Features in One Week

Summary: a small survey of demand generation users shows that more than half deployed basic demand generation features within one week, and about 75% within one month. More complicated features take longer, but in general, 80% of the features ever deployed are in place by the end of two months. This suggests that marketers are quickly gaining value from their systems, but also highlights the need for continued training to be sure they take advantage of all system capabilities.

*********************

Yesterday’s post described the responders to my online survey on demand generation implementation. Today we get to the main event: what people actually do.

Table 1 shows the actual responses, with the items ordered by % used (that is, how many respondents ultimately deployed a given function).


table 1

How soon after starting implementation did you first do...
first done:

first week

first month

second month

third month

later

never

total

% used

outbound email campaign

22

8

5

1

0

0

36

1.00

campaign response reporting

12

15

3

2

4

0

36

1.00

lead transfer to CRM

18

5

8

0

2

2

35

0.94

CRM integration / synchronization

23

4

2

1

3

3

36

0.92

landing page

19

9

2

0

2

4

36

0.89

lead scoring

12

7

3

0

10

4

36

.89

multi-step lead nurturing campaign

8

10

7

2

5

4

36

0.89

Web site analytics

14

7

6

2

2

4

35

0.89

Webinar campaign

5

13

5

1

6

5

35

0.86

campaign ROI reporting

7

11

3

0

8

6

35

0.83

data cleansing process

10

7

1

3

7

8

36

0.78

pay per click campaign reporting

9

5

1

2

6

12

35

0.66

Web page survey

3

6

5

1

6

15

36

0.58

email survey

2

2

6

1

7

16

34

0.53

combined

164

109

57

16

68

83

497

0.83



Looking at the table, we see:

- virtually everyone (more than 90%) does outbound email, campaign reponse reporting, lead transfer to CRM, and CRM integration. No surprises there.

- Just slightly fewer (80-90%) do landing pages, lead scoring, multi-step lead nurturing, Web site analytics, Webinars and campaign ROI reporting. I’m a bit surprised to see Webinars ranking so highly, given that support for them is rather limited in many demand generation systems. But they’re certainly a popular marketing tool, so I guess people will run them through their demand generation system regardless. The high utilization of other relatively advanced features is impressive (lead scoring, lead nurturing and ROI reporting), although perhaps to be taken with a grain of salt.

- Other features are less widely employed (53-78%), including data cleansing, pay per click (PPC) campaign reporting, and Web and email surveys. The latter three make sense: it’s hard to get PPC costs into a demand generation system, so many people probably don’t bother. Surveys are simply not that common, bearing in mind that most data is gathered through forms on landing pages. On the other hand, the relatively low utilization of data cleansing is a bit scary because I strongly suspect nearly everyone needs it. This may reflect the fairly limited data cleansing tools in most demand generation products.

So far so good. But the main purpose of the survey was to understand when and how quickly the different functions get deployed, to get a more nuanced view of the implementation process – and, in particular, see what marketers can realistically expect to accomplish in the first week.

Table 2 addresses this by calculating the cumulative fraction of responders who had deployed each function by each milestone (one week after implementation, one month, two months, etc.). The calculation excludes people who never deploy a given function, since we’re trying to understand how quickly the people who use a function deploy it.


table 2

cumulative deployment rate (base: ever deployed)

cumulative %

first week

first month

second month

third month

later

% used

landing page

0.59

0.88

0.94

0.94

1.00

0.89

outbound email campaign

0.61

0.83

0.97

1.00

1.00

1.00

CRM integration / synchronization

0.70

0.82

0.88

0.91

1.00

0.92

campaign response reporting

0.33

0.75

0.83

0.89

1.00

1.00

lead transfer to CRM

0.55

0.70

0.94

0.94

1.00

0.94

Web site analytics

0.45

0.68

0.87

0.94

1.00

0.89

multi-step lead nurturing campaign

0.25

0.56

0.78

0.84

1.00

0.89

Webinar campaign

0.17

0.60

0.77

0.80

1.00

0.86

data cleansing process

0.36

0.61

0.64

0.75

1.00

0.78

pay per click campaign reporting

0.39

0.61

0.65

0.74

1.00

0.66

campaign ROI reporting

0.24

0.62

0.72

0.72

1.00

0.83

Web page survey

0.14

0.43

0.67

0.71

1.00

0.58

lead scoring

0.38

0.59

0.69

0.69

1.00

0.89

email survey

0.11

0.22

0.56

0.61

1.00

0.53

combined

0.40

0.66

0.80

0.84

1.00

0.83




I’ve arbitrarily chosen to highlight when each function exceeds 75% utilization. This shows the relative deployment speed and presents a very interesting pattern:

- the basic demand generation activities needed for a simple email campaign (outbound email, landing pages, CRM integration and response reporting) are almost fully deployed in the first month . In fact, about half the users deploy them in the first week.

- Lead transfer to CRM doesn’t quite make the one month cut-off, but it’s also deployed by half the people in the first week, and almost everyone by the second month. Clearly moving leads to sales to a core demand generation function. The somewhat slower deployment, if it’s anything more than noisy data, might reflect the added time needed to set up a lead transfer process in cooperation with sales. You’ll note that the preceding four items were totally under marketing’s control.

- Web site analytics shows a pattern like lead transfer: nearly half the people do it immediately, but then there is a lag until it reaches nearly 90% deployment in month two. This might also reflect the need for help from the an outside department (whoever runs the company Web site). It might also reflect relatively low urgency, since other Web analytics tools are often in place. But bear in mind that detailed activity tracking of individual Web site visitors (not provided by traditional Web analytics) requires the demand generation tracking code to be installed.

- Multi-step lead nurturing and Webinar campaigns are both fairly complex projects, so it makes sense that deployment of these builds slowly and steadily through the first few months. We can probably infer that most marketers start with something simpler and then add these as they become more proficient with the systems.

- Most of the remaining items (data cleansing, PPC reporting, Web and email surveys) are relatively low priority, as reflected in their % used scores, so relatively slow deployment makes sense. The two exceptions are campaign ROI reporting and lead scoring, which have high ultimate usage rates (83% and 89%) but take a long time to reach those levels. Both are relatively complicated and require cooperation from external departments: ROI reporting needs revenue from sales and approved formulas from finance; lead scoring needs coordination with sales management. I think it’s reasonable to conclude that the importance of these items pushes marketers to deploy them, but their complexity and the need for external cooperation slows the implementation.

Is there a trend in deployment speed over time? I did some analysis of results by implementation year, and the pace does seem to be picking up. But it's a tricky analysis since more recent implementations haven't had time to deploy the longer-lead functions. I'll revisit this if time permits and let you know if I find anything.

Table 3 is similar to table 2, except that the fractions are calculated including never-deployed cases. This gives a more realistic view of the actual pace of deployment for different features. The sequencing is pretty much the same as table 2, with the notable exceptions of lead scoring and campaign ROI ranking somewhat higher.

table 3

cumulative deployment rate (including never deployed)

cumulative %

first week

first month

second month

third month

later

never

outbound email campaign

0.61

0.83

0.97

1.00

1.00

-

landing page

0.53

0.78

0.83

0.83

0.89

0.11

CRM integration / synchronization

0.64

0.75

0.81

0.83

0.92

0.08

campaign response reporting

0.33

0.75

0.83

0.89

1.00

-

lead transfer to CRM

0.51

0.66

0.89

0.89

0.94

0.06

Web site analytics

0.40

0.60

0.77

0.83

0.89

0.11

multi-step lead nurturing campaign

0.22

0.50

0.69

0.75

0.89

0.11

lead scoring

0.33

0.53

0.61

0.61

0.89

0.14

Webinar campaign

0.14

0.51

0.66

0.69

0.86

0.11

campaign ROI reporting

0.20

0.51

0.60

0.60

0.83

0.17

data cleansing process

0.28

0.47

0.50

0.58

0.78

0.22

pay per click campaign reporting

0.26

0.40

0.43

0.49

0.66

0.34

Web page survey

0.08

0.25

0.39

0.42

0.58

0.42

email survey

0.06

0.12

0.29

0.32

0.53

0.47

0.33

0.55

0.66

0.70

0.83

0.17



Summary

Pulling back from these details, what I find really impressive is how quickly in general the features are deployed: 40% of the features ever deployed are deployed in the first week; two-thirds are deployed in the first month, and 80% by the second month. An optimist might argue that this shows marketers are quickly gaining value from their systems. A pessimist could say this shows that marketers learn a few things quickly and then stop.

The slow-but-steady deployment of complex processes like ROI reporting and lead scoring suggests that neither view is quite accurate, since marketers do add some features over time. It’s also true that this survey didn’t capture some of the more esoteric demand generation applications that marketers might add later. So it does seem there is at least some continued development after the initial implementation.

Circling back to the original question of how much marketers can expect to accomplish during the first week, the short answer is: quite a bit, actually. But it still takes a couple of months to get fully up to speed, and there is certainly a need for continued training to ensure you get the full value of any demand generation system. The job is far from done the day the implementation team walks out the door.

0 Demand Generation Implementation Survey - Background Results

I've been having a dandy time analyzing the results of my Demand Generation Implementation Survey. Responses are still coming in but I thought I'd at least post some preliminary results to whet your appetite. Hopefully I'll be able to post a more substantive analysis tonight or tomorrow.

As of April 29, I've received 40 responses, of which I've discarded two as incomplete and two because they related to vendors I considered irrelevant (Zoho and Ad Giants PitchRocket). Obviously any survey based on 36 net responses (and self-selected at that) has little statistical value, but I still think the broad results are extremely interesting.

The survey was promoted on this blog and the Raab Guide site, but primarily via posts on Twitter. (Thanks to the many people who 'retweeted' the request). This introduces yet another source of sample bias. One measure of this is the distribution of vendors reported by the respondents, which clearly doesn't reflect the installed base of the industry. This distribution actually pleases me, since it means we have results from users of many different systems. (Obviously, however, the quantities are too small and sample bias too significant to break out results by vendor.)


nbr responses vendor
8Marketo
6Eloqua
3Genius.com
3LoopFuse
3Pardot
2Market2Lead
2

Treehouse Interactive

1eTrigue
1Vtrenz (Silverpop)
7No Response
36


Another intriguing bit of contextual information is the deployment date of the systems. Two respondents actually reported future dates -- I'd guess those were typos but, since responses were anonymous, I couldn't ask. There was actually another dated 6/01/2208, which I treated as 2008.

I was also curious to see the six responses for implementations during 3/09 and 4/09; obviously, these companies haven't gotten past their first or second month. Most of the answers for those entries reported features deployed within the first two months, or made the reasonable selection of 'later', so they could quite well be accurate. One repondent reported deployment on 4/24/09 (i.e., last week) but showed several features as deployed in month three. I assume represents their plans rather than reality. Fair enough.

In any case, the ten deployments in the first four months of 2009 (or 12 if you count the two future dates) and 12 in 2008 highlights the newness and fast growth of the demand generation industry. There were just five earlier deployments, including one for 1990, which is almost surely an error.


nbr responses

deployment date

1

10/09

1

8/09

3

4/09

3

3/09

1

2/09

3

1/09

12

2008

2

2007

2

2006

1

2005

1

1990

6

No Response

36



One final bit of more data, this more substantive: I asked how well their experience with deployment and their systems as a whole had met their expectations. Results strike me as extremely positive -- about two-thirds rated both experiences as better than expected, with just a bit more satisfaction with the systems than the implementation. Only a couple of responders felt things were worse than expected. Again, we have to consider sample bias. But even so, this seems to be a pretty happy set of campers.

I actually looked to see if there was any relationship between deployment year and satisfaction, and it newer customers may be a bit happier. But the numbers are very small, recency may also introduce some bias, and in any event even the earlier customers are highly satisfied. So I don't consider this more than a hint of what might be the case.


How would you rate your experience with...
%

better than expected

about as expected

worse than expected

total

system implementation

0.64

0.33

0.03

1.00

the system itself

0.67

0.28

0.06

1.00




How would you rate your experience with...
nbr responses

better than expected

about as expected

worse than expected

total

system implementation

23

12

1

36

the system itself

24

10

2

36