/ Advancing Analytics: The Journey to Improved Customer Intelligence

Advancing Analytics: The Journey to Improved Customer Intelligence

There is a wealth of insights and intelligence that lay just beyond the mass of structured and unstructured data in today’s enterprise. Savvy marketers are realizing that harnessing this intelligence through analytics is creating deeper, more beneficial relationships with their customers.

Here is what the webinar covers:

  • How to find best practices for creating advanced analytics
  • How to know what organizations can get your company advanced analytics
  • How to emulate market leaders who are currently utilizing analytics effectively

Transcription:

LIZ:      Hello everyone and welcome to our web cast. We want to thank everyone for being with us today and sharing the next hour with us. I want to also welcome everyone who has been attending the Bright Talks CMO round table and summit[JD1] , we know there’s been a lot of information shared today and we want to keep that ball rolling.

So what we’re going to do over the next hour is really delve into an area of conversation that has really become top of mind for most senior marketers and that is around analytics. The reality of analytics in today’s world is that we really need to understand what our intentions are, what our goals are for analytics and really understand how we can take that next step. So what are we going to do today? What we’re here to do is really understand how we can take those intentions to advance analytics, identify the best practices for getting us there, hear from some experts who can help us get started, hear from some marketing leaders who are actually getting it done, and we want to ask questions and I really do mean that. We want to see a very interactive session so we will be fielding questions from our audience and making sure that we get to as many of those as humanly possible within the time allotted. So please be sure to enter in any questions that you have for our speakers into the question panel in your viewer.

So marketing’s mandate has really revolved around a couple of core areas that’s been handed down from senior management. So what we’ve really been at work doing right now has been improving yield, accountability, collaboration and control within the global marketing organization, so it says 47% of marketers who responded to our yearly state of marketing study.

We’re introducing formal marketing performance management system, so MPM dashboards have really become something that we’ve come to rely on to be able to track effectiveness and impact of our marketing spend. We’re also implementing lead generation systems to better target and acquire business opportunities. And this is according to 36% of the marketers who again responded to the state of marketing study.

But where we’re really getting serious and where we’re getting our marching orders is that senior management is expecting marketing to lower costs and improve efficiencies. We’re looking to grow and retain market share. We’re looking to drive top line growth and we’re looking to keep the sales pipeline filled with high quality leads. And most importantly we’re looking to do all of this smarter, faster, and with more efficiency and more impact.

So how we plan on getting there, according to the state of marketing study, is that we’re looking at better segmentation, we want to integrate customer intelligence into every aspect of our marketing plans and our marketing strategies. We’re looking into market insights, what is the voice of the customer telling us where we need to lead? And we’re looking into bring on additional talent to gather, crunch, and manage data.

So data has really taken on a core central role into the world of marketing. However we’re really needing to advance where we are and how we view analytics. Marketing today is very comfortable with looking at a core set of analytics that really tend to look at where we are on the surface, whether it’s clicks, or whether it is views, likes etc. But, we really need to take that next step and that’s what we’re here to talk about today.

So when we asked marketers “What were you doing to, were you able to fully leverage analytics to improve performance and decision making?” 30% said that they were able to do this. Now, when we asked those marketers who felt that they were excellent in their digital marketing performance, we found that 41% of marketers were actually implementing systems that were able to fully leverage analytics to improve performance. You’ll see there’s quite a significant jump, so analytics is playing a role in those people who feel that they are excellent and superior in their performance abilities. But we also took a look at the other side of the table and we found that of those marketers who were still questioning the value of their investment and the impact of their marketing strategies, only 20% were actually leveraging analytics to improve performance.

So again, I think the numbers speak for itself at least in our minds that analytics are improving performance, they’re getting us to be smarter, faster, better at all of the things that we need to do, but more importantly ,analytics are really advancing the role and the cause of marketing within our organizations.

61% of marketers that we asked intended to increase investment into the tools and platforms that enabled improving segmentation or targeting. Because again we’re looking to do our jobs faster or smarter, we’re looking to eliminate waste and we’re looking to track and accurately measure across the marketing eco system. So who are our experts that we’re going to be speaking today?  We’re going to be hearing from Rich Smith who is the Senior Vice President and CMO at AIG Bank. We had hoped to have Bob Page who is the VP of Analytics for eBay but it seems that there may have been a last minute conflict that has come up, so I do not believe that we’re going to have him on the session today. But we are going to hear from ….

BOB:                            Yeah Bob’s here.

LIZ:      Oh Bob, great excellent, sorry I apologize folks, I eliminated Bob from our speaking line up very accidentally, this is what happens on web casts when you can’t see people. Yeah, Bob is here. And Chris Wintermeyer who’s the Senior Director of Enterprise Solutions at Domo. Each of these speakers, I’m very excited to say, has a very unique sense of where analytics fits not only within an organization, but how an organization has embraced analytics, and how they’ve advanced analytics within their own marketing structures. So without further ado I’m going to pass this session off to Rich who’s going to talk to us about how AIG Bank has integrated analytics into their marketing system.

RICH:   Alright, thanks Liz and good afternoon everybody, I’m happy to be here with you today, I think what I’m going to talk about over the next few minutes is really about how you get started. I think Liz gave a lot of the background as to you know why marketers are seeking to advance their analytics within their organizations and I’m going to speak a little bit about how culturally you begin to make the case within your organization and what maybe some of the first steps are. I think the other presenters are probably focusing a bit on the tonnage of data which certainly eBay has and some of the technical aspects of how you manage and work with the data. But when it comes to integrating in analytics into your organization, I really kind of looked at it in four steps.

You know first is building the initial business case then including it in all of your campaign planning. The third step is marketing and communicating the value of the analytics and the results that you’re getting out of it internally so that you kind of complete the cycle and free up more investment dollars and more resources to invest in building your analytics methodology even further. And then lastly, embracing advanced analytics, once you get past the first steps to really start to unlock the value and improve your marketing ROI. So let’s kind of jump right in.

First off, building your business case or building the value proposition, I mean I think it’s beyond old news now that you know marketing is accountable, that senior management and the [inaudible 00.08.01] [JD2] is looking for marketers to prove their worth and prove the value of the marketing investments that they made. So really as you go to build the value proposition you start with your natural constituents, you know the CEOs, the CFO, risk management within your organization which could take a lot of different forms, finance and accounting. And these are the areas of the organization that typically are going to be the most interested in the value of measurement and quantifying your results.

Identify best practices in your industry, you know, what are your competitors doing? What are the key performance indicators that your industry looks at? What do they analyze? And perhaps even more importantly what are they not looking at? You know where can you gain a competitive advantage by analyzing a segment or looking at the business in a way that perhaps they’re not taking account of.

Enlist your other stakeholders. You know there are many parts of the organization that are going to be involved in implementing any kind of analytics regime, it can be operations, it could be your customer service area, your IT department, your CIO, they’re going to need to be involved in the project and you’re going to need to have them on board.

Seek outside solution providers. You know Chris from Domo will be on later and he’ll talk about some of the products and services they provide. But there are many different solution providers that can help you get started.

Estimate the cost benefit. Now this can be actually difficult. The costs are sometimes relatively straight forward but the benefits are a little bit harder because you’re talking about, you know someone that’s forward looking trying to project what the benefit of analyzing your business, increasing your analytics in your business are going to perform and you know my advice there is to start with you know a break even analysis. So, figure out your costs again relatively straight forward and then project out what kind of improvement you would need in your performance in order to justify that expense. And then just give it the readable test and is that achievable, is it reasonable to think that you’re going to be able to, that the investment is going to lead to benefits that will give you a return. And then finally present your case.

Next step is campaign planning. You really have to include your metric structure in every single campaign, strive for end metrics, whether, again if you’re talking digital whether it’s from impression all the way through a click and down the funnel through to a sale and then through repeat business, you’ve got to plan out every stage of the funnel. You don’t want to be these guys right, you have to think through all the various systems, all the various steps that a customer is going to take as they move through your sales process and make sure that your technology with your metrics can carry through every step of the way. Because if you leave any gaps at all in the process you’re likely to lose the value of the entire, of all of your efforts and not get anything out of it.

Gather and retain as much data as possible. I have, I’m always amazed whenever I go through any kind of model and exercise at some of the data elements that actually turn up as being relevant. So, the best bet is to retain as much as you possibly can. Retain as much data along the path, along the funnel about your customers, pull in external data sources—all of those things can be immeasurably valuable later on.

Plan your tracking scheme for growth. You know whether you’re assigning tracking codes to each key word in your search marketing, whether you’re putting tracking codes on direct mail pieces, you need to think through your tracking scheme and allow for growth, so that over time you can continue to use that same tracking methodology. You have to assign these codes in a smart way so that you can read them on the back end and interpret what they mean and make good use out of the data. And as you plan campaigns, you need to budget in tracking and analytics as part of your campaign expenses. Just include that upfront, make it just a part of doing business and it will become a part of your organization’s culture.

Market internally. The best way to continue to get visual investment dollars for analytics is to market the results of what you’re currently measuring and the benefit that you’re getting out of it and create that kind of virtuous cycle where you know your marketing reports and your literature reports are sought after by the CEO’s and CFO, and other members of senior management. This becomes a part of doing business and relied upon to steer the business. When you get to that point culturally you’ll be in a very good position to keep getting the investment that you need, to keep improving your ability to analyze your business and drive those results. Very, very important as a marketer to continue to market internally and just assume that everybody knows what you’re measuring and the people know what you’re doing and that they know that you’re delivering value. Make sure that you put those reports in front of them and demonstrate that you’re delivering value and how your analytics are delivering value.

Communicate that the actions that you’re taking and the results that you’re getting out of it and try to quantify that value. Quantifying, can sometimes be difficult because in many cases you’re proving the counter factual right. You’re trying to say “Well you know we would have been worse off had we not had our analytics tools and this is how much we’d be worse off” and that’s sometimes difficult to do, but you need to go through that exercise and perhaps compare it to past campaigns, look at lifts that you’ve gotten instituting new campaigns or out of the decisions that you made based on your analytics.

Lastly, embrace advanced analytics to begin to really unlock the value. And I think some of the later presenters are going to get into this a little bit further, so I won’t do too much of it here, but customer segmentation and preference modeling, and lifetime value models are very, very important to begin to assign lifetime value scores to your customers and to your prospects and to your leads. This will really allow you to unlock additional efficiency and get much better at what you do. And also get into applying optimization methodology, I just threw up a simple one there which net present value divided by cost per account is equal to one, so in other words, if you get to the point where you are calculating lifetime value on prospects and using that to determine how you allocate the investment dollar, marketing investment dollars, your one simple tool it’d take the lifetime value or the net present value of the customer and divide it by the cost to acquire that customer. If that calculation comes out greater than one, then that would be a prospect that adds value to your organization and one that you’d want to invest marketing dollars into acquiring.

And lastly, a rapidly expanding area particularly due to integrated multi-channel marketing is the whole aspect of attribution. It’s very difficult at this point, but incredibly important as we begin to do more and more multi-channel campaigns to really try to allocate credit to different marketing channels for the eventual sale. You know if you are doing search and display and perhaps you know billboard or broadcast TV in a particular market, which of those channels is contributing to the sale? There are tools and techniques out there now to help you track these things and begin to analyze them, but the whole field of how you assign value to those different channels and do it into the ultimate sale, is expanding rapidly and you’re going to need to work with in your organization to come up with your own methodology to really begin to efficiently allocate your marketing values across channels. So with that I think I’m going to turn it over to Bob from eBay who will take you through his personal presentation.

BOB:    Thank you Rich, I appreciate it. Let me first say that I suspect the folks of this call know who eBay is but I wanted to just maybe level set on a couple of things. eBay is known as a sort of story history in Internet culture around sort of the place where you sell what’s possibly in your garage. However while that’s still true and hopefully will always be true given it’s our legacy, you might not be aware that most of what we sell is new and most of what we sell is fixed price, not auction. The other thing is that we’re increasingly seeing more cross border sales where say someone in the UK might buy something from someone in Canada, or maybe more typically someone in the US might buy something from a seller in China and we see some swings of how that works based on things like the exchange rate of money etc.

So very interesting, very global and with that is also the technology component. I won’t go into a lot of details about this other than just to have the slide impress upon you that we have a lot of data. We have 300 + million items live on the site at any one time and there’s a lot of data that we’re collecting. I should also say that part of this, and this is sort of somewhat technology as well, is I would be remiss if I didn’t talk about mobile and what mobile has done to eBay, you know what eBay has done with mobile in the last few years. About 25% of our transactions are actually conducted, meaning the buy/purchase button, was pressed on a mobile device in 2012, in fact we will do probably over 10 billion dollars in 2012 via mobile and we have people buying cars and boats and islands and all kinds of things via mobile. It’s really taken us by storm and we invested heavily into it several years back and we are seeing the value of it as more and more folks use mobile in their everyday shopping, and that significantly is changing the way we approach our marketing as well.

Just to maybe give you an example of that, when we issue an email we now have to assume that that email, whether it’s through a campaign or whether it’s through a piece of information that says “You’ve been outbid” or whatever it might be, we have to assume that that email is being viewed on a mobile device and so if there’s a call to action in the email and that call to action links back to the site, we need to make sure that that is actually being linked to something that is mobile aware and not say a generic home page or a page that says “Oh how would you like to download our mobile app?” because then we lose the context.

I’ll move on from there. So, I want to talk about four specific things that we learned to drive a better experience, and when I say better experience it really has to be around the users. So let me talk about the first one. I don’t want to mince words here, we built it and we invested in it and it is expensive. If you feel like getting a return, and I liked Rich’s message in his phrase “explode ROI,” I think that’s great. But clearly it’s not an overnight thing, you need to think about it ahead of time and you need to invest in it and yes it is expensive. We look at it from four different places. We’ll call them the pillars of our analytics.

The first is around reporting. The intent here is that for the most part what you’re going to be reporting are things that you understand ahead of time. It may be campaign performance, it may be the amount of time someone spends doing whatever it is that you want them to do etc. It may be sales, conversions etc. Those are things that you’ve already decided that you are, have created KPI’s around and you’re going to be measuring, collecting the information in a structured way, storing it, building the dashboards—all this stuff is automated, You want your IT organization to be or your outsource vendor to be sort of on the ball and providing this as cheaply as possible I guess, or inexpensively if possible, because it is something that you’re going to see either every week or every day or every hour or how often it is that you want to look at this. And for the most part these are things that everyone in your organization is going to consume.

The next is around analysis and not all teams do this, but these are things that are using a lot of rich data sets, it may not be the structured data and it may not be the data that you even have considered. Again I’ll go back to Rich when he said he was surprised to unearth gems from data that were collected in a way that we didn’t really know ahead of time what we wanted to look at, but in the end there it was, we found some interesting patterns. A lot of this stuff is done by analysts for the decision makers;  it could be the CMO, any in the C sweep, who’s looking to understand beyond some of the basic reporting, or what’s driving that or if there are gems uncovered by the data tis ypically done by some data scientist or some analysts or sometimes even developers.

Next is testing and I pull out testing specifically because I think that this is where a lot of the innovation comes from, we’ll have ideas, something will come from the analysis for example that will show a correlation. Well just seeing it as a correlation doesn’t mean there’s necessarily causation. So we’ll then run a test and we’ll see with a small sample of the site, is it in fact the case that there is a causation and can we improve the user experience through some of the testing that we do? This is significantly driving our innovation where we take small steps and sometimes we realize we’re probably going in the wrong direction. Or we learn and we can iterate from that and make it even better. This allows us to get things to the site faster or our campaigns on a broad scale quicker than issuing something fast and then realizing “Oh we kind of messed it up.” This for the most part is while it’s the markers who are looking at this, our developers do too, our developers may have some ideas of things that they would like to do and then in consideration with things like our product management team or our marketing team, may come back and say “This is the way we want to think about this, these are the metrics that we want to measure as part of this test” and it could be just user engagement but it could be anything else, conversion, what have you.

And then finally all that is great, but ultimately we want to get it to a place where we are doing this in production and that means targeting, it means segmentation, and it means optimization. Again I think Rich covered that quite well in some of the techniques that he mentioned here. The goal obviously is around not necessary “How do I optimize a campaign that this campaign got X number of clicks or whatever it might be, but how is the customer experience around that campaign?” And what we’re really talking about there is being able to not measure from the activity of the campaign but the end result on the customer, which is ultimately what we’re all after.

So that’s one, the second really is getting the data and keeping the data. We have I’d say three years ago, not to air too much of the dirty laundry, we did not have the systems or even the techniques in place to keep some of the data that we now believe is significant and necessary and has changed the way eBay works. We were keeping all the marketing data, you may recognize that we do a lot of key word buying on some of the major search engines, display ads etc., so we have a lot of detailed information about our marketing and how well those were working, email etc. We also had a lot of information about the specific transactions that were happening, but we were not keeping the full number of components that are behavioral in nature. The clicks on the site for example, the searches once people got to the site, these kinds of things, not knowing those is like having someone wander through the grocery store and when you leave what you have as the grocer is what products they bought. That’s very interesting, but it’s not enough, you’d like to know how often they come to the store, how long did they stay in the store, what aisles did they walk down, what did they look at and then put back on the shelf? These behavioral things will let you understand their interests, their impulses, their motivations and that end to end picture from marketing through behavioral transactional, and I’d say even through support, are going to be very important for us to unlock a lot of the data that is sort of set aside and the behavioral stuff is what explodes the amount of data that we have, because it’s not just transactional, it’s also things that did not lead to transactions.

So the third is the experimentation and discovery component can’t be understated. If you’re just working to optimize the KPI’s that you have, that’s great, that lets you get to ROI, but there needs to be a certain level of discovery if you will and in our case we have used experimentation extensively, but we’ve also used, because we now have so much data we’re able to say “Are there things in the data that we’re not looking to test, we’re just uncovering things?” And I’ll give you an example of one, not really into the slide actually. We found that on auctions sometimes the sellers were listing multiple items identically and analysis showed that if we were able to stop that and not have our customers exposed, the buyers exposed to duplicate listings, everybody won because the prices, final prices paid generally were higher because there was more engagement by the buyers.

And so we instituted a policy without any running any experiments at all to say this is the right way to go, we did that through just pure analysis and this wasn’t about opinions, this came right directly out of the data. And this slide that you see here really is something that we’ve significantly launched almost every aspect of eBay from registration through checkout, through almost every component of it based on feedback from our users yes, but also a lot of data that we got through extensive testing and this particular slide is, shows some of the personalization that we are doing now on the site where this individual may be interested in Victorian door hardware and here it is, they have a nice rich experience in their browser.

And then finally let’s not underestimate the fact that it does require a lot of talent and a lot of infrastructure as well. It’s not enough to go to a vendor and say “I want to buy a system, put it in place and think that you’ve finished, it’s going to require a lot of talent and it’s going to require you to think about what it is you want to keep, how long do you want to keep it and then how do you want to use it? That’s really the four things that have been beneficial to us and to our recent success. And with that I’ll throw it over to Chris.

CHRIS: Thank you sir. So, great insight by the way from both Rich and Bob. I’ve been working with customers in various BI aspects for a couple of decades now and I think this insight’s just phenomenal. From my perspective specific to marketing, one of the big things that, this goes without saying but I’m saying it anyway, is from an explosion of data standpoint and that is, you know we hear IT talking a lot about big data, that you know it’s all about the amount of data that has to be sifted through, but it’s not just an IT issue. This directly affects folks in marketing across the board. You know it’s not just the volume of the data, but it’s the various types of information that have to be correlated and coalesced to be able to get a full view of what customers look like and then also the velocity of that data.

And, we did a study not that long ago and some snippets of that are over on the right hand side of the slide. The one that shocks me the most is that every minute are the numbers that you’re seeing here represent what happens in a minute of any day. There are 204 million email messages sent and that’s just one example of the volume of information that we’re dealing with on a regular basis. And being able to bring that together when you’ve got so many different tools that you’re using to try and get a bigger picture of what’s going on, how do you collect and aggregate and how is all of that data? You know when we’re looking at things like Eloqua and Marketo and Adroll not to mention you know Google Adwords and Analytics and bringing all that information together. But then being able to look at the big picture and get that data reliably, and be able to validate the information that you’re looking at so that you get this big picture of what’s going on.

It’s the pain that I see constantly with customers that I deal with on a regular basis, there’s a large retailer in Texas that not that long ago I was working with and they had access to a lot of information, in fact from several of the sources that you see on the screen here, but the way they actually coalesce the information was to print out various reports from the different systems, pin them up on a wall that was literally, the entire wall was literally covered in corkboard, and then they would stand back and look at the charts to try and connect the dots. That was the way that they, until we started working with them, we’re actually trying to look at the big picture customers.

And so it’s getting access to the information but also understanding exactly what it is that you need to measure and how to measure that to be able to do your job more effectively and to be able to basically reach what we call marketing nirvana. And so what I want to talk to you about is how do we get the right data, how do we get it in one place and then how do we look at that in the right time so that we’re getting that big picture?

And there are basically four steps as we see it to being able to achieve marketing nirvana and the first is, you need to know what you want to measure and it seems very simple but in reality, in practice the folks that I deal with on a regular basis, this is surprisingly non-existent in the majority of prospects that I deal with. You need to map out ahead of time what it is that you’re going to be looking at and then worry about having the right processes and tools in place to be able to collect that data. So the very first thing you need to understand is, what is it that we want to look at? And really best practices from my perspective, really focus on four things. And the first of those is volume. We need to know how many people are in each stage of the pipeline, how fast they’re growing over time and how many people are being added in each period. If you analyze that, you get visibility into the activities that are contributing most to new people in each of those stages. There’s a B to B technical leader that we worked with that they use volume data to learn that half of the people who buy their products, they sell cyber security products, and that half of the people that buy those products participated in at least one online demonstration before the purchase. And so that is actually steering their direction, to steer folks to see a demo before they reach out for that buying stage.

The second is conversion and that’s you know, measuring conversion rates from stage to stage and the trends over time and this allows those of us in marketing as well as sales leaders quite frankly, to analyze where the leaks are in the pipeline and then what each member of the team and then what each team can respectively do to help reduce those leaks. And it also helps optimize the stage movement criteria, the things that help you identify which types of leads are converting at the highest rates. There’s a consolidated organization that analyzes conversion rates of marketing leads all the way through to sales accepted lead and it refines the criteria for what is considered sales ready, basically. And that ensures that sales is working on the reach with the highest likelihood of actually turning those into revenue, right, actually being able to see a profit from it.

The third is velocity. And this is measuring the average time it takes for a sale to close, how fast people are moving to those stages, and then also how much time in the stage and how that’s trending over time. And we need this information to be able to find the choke points in the process and also be able to determine how to better serve the needs of the buyers so that we can reduce those choke points over time.

There’s a marketing leader that we worked with that was using measuring or using the velocity data, it was at a commercial bank, to realize that they have a 130 day cycle time between the first touch all the way through to win. And so the bank took a step back to analyze how that velocity varied by industry and geography so that they could optimize ways to shorten that velocity time for various targets that they were going after.

The fourth one is value. Marketers need to know the total value of their revenue pipeline that also includes the value in each stage and how it increases or decreases with each period. If you analyze that data, the marketers can ensure that they’re targeting the highest value segments and positioning the value of those products and solution throughout that line cycle. Using metrics on the value of the pipeline, a customer of mine was actually able to analyze the average deal size changes through those various stages and it fell that in the early stages, the value can be quite big but as the stages progress that value shrinks. So they found some ways to help the sales reps maintain that deal value so that as the prospect moved through to the later stages they weren’t losing that value as they actually went through.

The second step to marketing nirvana really focuses on collecting and tracking the right data. I’ve worked with customers across the board who automatically assume that “Well if we’ve got the data then we need to be able to analyze it, we need to be able to find dots that we can connect even if none actually exist”. And that’s actually a big mistake; I mean you know what Bob was talking about eBay nine petabytes of data, that’s stunning to me. But the real value is knowing what it is that you need to look at within that nine petabytes, not just trying to analyze all of it.

And so one perspective that I think really helps is take a step back and look at what are the most important decisions that either you or your CXO’s are making on a regular basis? Start with that, and then from there you can determine the metrics and the KPI’s and the measurements that you actually want to be able to keep track of. From there you then can determine “Okay what sources of data are going to help us reach that particular decision?” It’s much better to start from that perspective as opposed to saying “Alright, we’ve got all this data, let’s just dig in and see where the patterns are.” And it’s real simple folks, the bottom line is if you can’t tie the data that you’re looking at back to company goals, and that can be as simple and as high level as things such as revenue and profitability, you need to ditch it. It’s not something you need to be looking at in terms of measurements from a marketing perspective, you’re going to get lost in details that don’t actually matter.

The third step and this is one that Domo feels very passionately about as do I personally, and that’s sharing the love and we share that love through data democracy. And that’s basically as simple as making sure that people have access to the right information but also giving them the ability to share and that’s not just the data or not just reports, but also information about what it is that they’re looking at. They need to be able to share perspectives and insights and capture that so that, that can then be used as part of the information that you’re actually looking at.

  • Without the ability for folks to collaborate and communicate on the information that you’re looking at, you’re not necessarily getting that single version of the truth, everyone may be looking at the same report, but if a lot of the insights are getting lost in text messages or email sent messages, then you’re actually missing a big perspective of what it is that you’re looking at. So you need to consider “How are we capturing that information about the insights that people have as they’re looking at the data that we’ve made available to them?” And once those three things are in place then it’s time to talk about “Well what is the technology that’s right for us, what will then drive that?” And there’s obviously key factors that you want to look at and there are four bullets here that I consider to be more important just in my two decades of doing business intelligence and working specifically with sales and marketing organizations.
  • And the first is can I access the information in the various sources that we actually need and provide that in either real time or in the time that we need to be able to make effective decisions?
  • The second is, can I get access to what I need and then modify it or look at it in a way that makes sense to me without getting stuck in some tube, or being placed in some backlog? Do I have to wait five days to get a new view of a particular report or chart that I’m looking at or is it something that I can actually do on my own?
  • The third is, as the information rolls out to more folks in the organization, as you start to bring different departments in to gain their perspective and start everybody working towards the same corporate goals, can you scale with the technology that you have and can I apply group and role-based permissions so that the right folks are looking at the information that they’re supposed to see, but we’re not necessarily sharing things with certain people that shouldn’t be shared.
  • And then the fourth is, and this one it shocks me, every day when I talk with folks who say “Yeah I get access to the information that I need, I log into this system and get this piece of it and then I log into this system and I get this piece of it and then I log into this system to get the final piece of it.” And to me that’s just insane, I don’t, I couldn’t imagine doing business without being able to grab information from the various sources I need and then literally combine it or coalesce it into a single chart or a single report as opposed to me having to print out multiple pieces of paper and lay them out on a desk or look at multiple screens to be able to get the big picture. You should be able to get access to what you want all in one place. And yeah it sounds simple but it’s surprising at least from my perspective how many prospects I work with that don’t have access to that.

There are also some pitfalls that I see over and over that if you can avoid these you would do so at all costs because in the long run it’s going to just make you that much more effective. The first is don’t measure just the things that are easy, there may be some things there that are harder for you to measure and that could be because the data is more qualitative and quantitative and so there’s some work there that needs to be done. This could be that “I don’t have access to certain data sources so I’m just going to ignore that particular perspective or part of the business, that’s a huge mistake. There are some things that are difficult, and as Bob and Rich both talked about you know the process involves not just having that technology but having the right people in place and that’s going to help you drive getting to what it is that you need to measure and if you’re only focusing on the things that are right in front of you and ignoring a large part of it just going on gut feel obviously that’s not the most effective approach.

The other is tracking quantity over quality. This is something that I see time and time again, it’s not just about the number of leads. Our own company actually was guilty of this, less than two years ago where it was all focused on just the quantity “How many leads are we generating for sales?” It didn’t matter what the actual quality of those was, it was all just based on the numbers. And we learned, and just as many other organizations have learnt, that it’s much more valuable to know “Well how fast are these leads converting and which leads sources should we be focusing on and which ones are generating higher revenue for us?” So just setting metrics or goals based on the numbers and not the qualitative information behind them, that can kill you.

And then the last one is managing the metrics instead of managing the performance. You know it’s great to be able to lock through the process and put all the information in place that you need but if you’re setting goals based solely on the metric numbers as opposed to actually measuring the performance of what those numbers should be driving, then you’ve missed the mark. And this is easier said than done, but being able to look at industry peers, being able to gain insight from what others are doing and then leverage that so that you can determine what’s the right way to measure to that performance, will actually make you a much more effective marketing organization.

And really from a Domo perspective there are six key things that we feel that folks should look at when they’re looking at technology based solutions, specifically involving the type of information that Rich and Bob talked to you about today. To reinforce the point that I said before it’s the right information, not just all your data, but having all the data that you need that’s actually relevant in a single dashboard, in real time and then also being able to get that on any device. Most of the executives that I work with now don’t even focus on consuming the information through a traditional dashboard on a desktop or a laptop, it’s all about tablets and it’s all about phones and it’s all about exception based reporting. I don’t want to have to sit and stare at twenty or thirty or fifty different reports or charts if the system can tell me what it is that I need to be focused on and alert me when things are starting to go wrong, now I can focus on higher value business within the organization and let the system do the work that it was designed to. And all of those things coalesced or combined will then provide you with that single version of the truth. And again, that goes back to sharing the information through the organization and including that qualitative aspect, not just the quantitative data that you’re actually looking at.

And if any of this sounds appealing to you, we’d love to talk to you some more. You know this is something we do every day and we like to feel that we’re pretty good at it. So you know feel free to reach out to us and we can talk more about how we have helped marketing organizations in a variety of industries become more effective and with that Liz I’m going to throw it back over to you.

LIZ:      Great, great, thank you. Well when I hear all of this from all three of you it sounds pretty dang easy but I think we all know it’s a lot harder, so I want to turn some time over to answering some questions that have come in from our audience. I’m going to go ahead and start with a question that actually when I saw it, it did make me laugh a little bit because I can specifically think of instances where I have seen this. But one viewer has asked, “Have you ever experienced data hoarding within organizations?” Chris I’m going to start with you. With the folks that you work with have you seen people kind of doing that data hoarding where they want to gather as much as they can but don’t necessarily know what to do with it?

CHRIS:    Yeah in fact I see it all the time and I’ll actually take it to the next level. There are some organizations that I’ve worked with that earlier on in the process the hoarders didn’t want to share, it was all about letting go and giving that information to the right folks. We see it on a regular basis and you know it’s a huge mistake. I mean I see why it happens, I understand the logic behind it but the problem is the business as a whole can’t run effectively when you have those hoarders, both in terms of “Give me as much of it as possible” and then also “I’m going to be the game keeper of it, if you want it you’re going to have to go through me.” And so being able to open that up and basically to use a cliché term that really is valid, to provide data democracy within the organization, it’s actually one of the biggest things you can do to make the organization more effective.

LIZ:      Yeah great, great. And another question has come in regard to would the presentation be available to participants afterwards? This presentation will actually be available on demand immediately after the web cast so you should be able to access that. If you have any other questions you can feel free to go ahead and reach out and email us for any other specific questions. I’m going to go to something that says, “Bob said save all the data, you never know what will yield insights.” Chris said, ‘Chuck what’s not relevant and stick with the data that ties back to your goals.’ Which one is right?” So I think I’m going to let the two of you hash that one out but Bob when you hear Chris says, Chuck what’s not relevant does that go against what you guys have been doing at eBay or have you really been just focusing in on the right data that’s getting you to those actionable insights?

BOB:    Well I mean it would be easy to say I disagree but everything is nuance, I mean the reality is if you’re keeping data that you’re not using then you’re just adding expense that you don’t need. If you have a commitment to trying to figure out if the data is useful or not or you believe that you might in the future, then you might as well keep it. Not everyone has that luxury or the benefit to be able to do that. But if you do, you just have to understand that once you throw data away it’s gone forever and you cannot extract any value from the data. You may say now you never will, and if that’s true and you never do and you make that decision, that’s fine and it’s probably going to save you a little bit of storage costs, but frankly storage is pretty cheap right now. And as long as there’s some ability and some way to say, “You know there might be some insights that are living in the data that we didn’t know to ask for ahead of time” so they don’t show up in a dashboard, then you know you’re going to unlock some innovation at some point, you might as well keep the data and that’s just where I am with it.

LIZ:      And Chris.

CHRIS:      So yeah, so Bob I was actually hoping that you would say you completely disagree, I was hoping we could get into a webinar cage match but what I mean….

BOB.    I’m throwing a chair at you right now.

CHRIS:     Quick somebody tag me out. So let me be very clear, when I talk about focusing on the right information in no way would I ever advocate throwing away data. Bob’s exactly right, storage is cheap and you never know what insights you’re going to gain down the road. I was talking specifically about the consumption of information on the front end, from the visualization and reporting aspect. What I don’t like to see prospects and customers getting into is “Well, we’ve got the data so we’re going to report on it, so I now have 455 metrics on my dashboard that I’m looking at” when it turns out only 28 of those are relevant are irrelevant. So without question the data itself from a storage perspective, I would advocate never throwing it away because Bob’s right when it’s gone, it’s gone. But from a consumption standpoint, from what I’m looking at on a day to day basis to run my quarter of the store, just because I have it doesn’t mean that I need to be reporting on it.

BOB:    Yeah I fully agree there. If you’re providing what amounts to screens full of numbers without context and open to interpretation that’s as bad as “I’ve got a full corkboard wall full of charts and graphs and numbers.”

CHRIS:     Exactly, exactly, that’s exactly right.

LIZ:      Great, great. So we have a question that’s come in and Rich I’m actually going to start this with you and we’ll go through all of our presenters here. But the question is, “How process oriented are you and do you tie data to process? For example have you identified customer focused cross functional processes?”

RICH:   Well yeah, I mean I think you have to be process oriented and I’m not exactly sure what you mean by customer focused cross-functional processes, but I’m going to interpret that to mean a process that might cross different functions of the organization or different areas. You know for example, sales and marketing. You have to in my experience it’s very important to track the hand offs between different functions in the organization, so marketing may bring in the lead, but then sales is responsible for handling that lead once it’s in the door. You need to be able to track the handling of that lead, the hand off between the marketing activities that generated the lead and then what area of the sales organization then took responsibility for it, what communication they had with the lead after they took responsibility for it, what different collateral was sent to them, phone communication, all the way through your funnel to eventual sale and then perhaps hand off to an account management area of the organization. So really understanding all those processes and having a way to track the full life cycle is extremely important.

LIZ:      Great, great. We’re running closer to the top of the hour so I want to be able to get in some more of these questions here, so thanks to all of you who are submitting these. We have a couple of questions here in regard to budget and I know that across a couple of our presentations today we talked about that sometimes this is not going to be an inexpensive route as far as implementing some analytics systems. But, the question really is around describing some of the costs and if you are able to describe those and practically speaking what are some of the low hanging fruit in analytics that we can start with to start justifying an ROI on analytics and Bob I’ll start with you.

BOB:   Well I’ll go back to the start of Chris’ which is about making sure that you know what you want to measure and creating the KPI’s that go along with that. You have to start somewhere. As long as your view of what you want to accomplish is outcome based and not activity based. If what you really want is increased conversion, that should be your first metric and then you need to start to ask the sort of five ‘whys’ you know “How do we get there? Measure those first and you’re going to start to expand your breadth of analytics but you need to do the sort of crawl walk around it and I think that first starts with “What do you want to measure and why?”

LIZ:      Great, great. Chris.

CHRIS:      I actually wholeheartedly agree with what Bob just said, I mean focusing on outcomes and then from there working back to what you want to measure is by far the most important thing. The only thing that I would add is, I deal with a lot of customers who say, “You know we know that there are certain things that we need to measure just based on what we’re doing in the business but we don’t know what we don’t know, Domo can you help us understand what we should be looking at?” And so regardless of the technology company that you choose as well as business partners you want someone who can bring industry expertise to give you a perspective on not just what you should be measuring, but also the things that you shouldn’t. And I think having that capability is something that’s pretty important or as important as the actual technology used to deliver it.

LIZ:      Great. And Rich anything to add?

RICH:   No I think I would just reiterate with what both Bob and Chris said, I mean I run into this or I talk to people all the time who say “Well you know, to implement these customer behavioral tracking methodology and systems, I mean the budget is just extreme and there’s no way that my business could start there or afford that to begin with” and I think the answer is don’t worry about that, get started. Walk and crawl, walk, run just as Bob said don’t let that be an impediment to you getting started, start at the end, you know work backwards from sales conversion and work backwards through your funnel and I think you’ll quickly find the low hanging fruit.

LIZ:      Great, great. Another question that’s come in is that in many or in fact maybe most organizations there’s often a chasm between sales and marketing departments. “Do the presenters have any recommendations for how to use data analytics to achieve a common view of the customer and lead and bridge this chasm?” Chris maybe you can start off with this one.

CHRIS: Yeah I’ll keep it short just given the time but that’s an excellent question and I wish quite frankly more people asked it. The answer is yes and it’s, for me it’s more about the process and the culture than it is the technology, you’ve got to get the folks in the room and decide on common definitions. What are we going to call an MQL, an SQL, an SAL? How are we going to define those, what is a customer, what is a lead, what things are important to measure and monitor. From there then going back to what I said about data democracy, having technology in place that allows you to share insight between those two areas of the organization will definitely help. But if you don’t have the process and the common agreement in place from a cultural standpoint it doesn’t matter how good your reporting on your data is.

LIZ:      Excellent, excellent. And Bob anything to add?

BOB:    No, I think he’s covered it well.

LIZ:      Okay excellent, Rich?

RICH:   Yeah no, I think my experience is just what Chris said, the difficult part is agreeing on those definitions, yeah you know what’s a lead, what’s prospect, where the handouts take place. Once you’ve bridged that between sales and marketing and you have a common view and share the data, I think it really helps to bridge that chasm because everybody’s working on the same sheet of music.

LIZ:      Great, great and I think we’ll have time to maybe tackle one more question and this one’s come in specifically for Bob: “How does eBay tackle info coming from cross channel platforms e.g. mobile versus desktop, and website. My understanding is that tracking abilities via mobile is limited. How do you handle that process as it relates to analytics?”

BOB:    Well it is a challenge. So obviously if the, if the customer is logged in then that makes it easy because they have an identifier, if they don’t then we have to use a number of technical techniques to try to link them together and if that fails then we have to you know sort of back off into less and less accurate ways of doing it but, the business says “Hey we really need this, we understand that there are technical limitations but we’ve got to have it” then the technical teams then just have to knock their heads together and try to figure out “How do we do it?”

LIZ:      Excellent, excellent. Well gentlemen thank you so much for joining me today for this hour, I really appreciate it, I think the insights were absolutely fantastic, so to each of you thank you and to our audience, your questions have been amazing, thank you for the interactivity here. This webcast will be available on line for consumption on demand really within the next five minutes. It’s one of the joys of being on Bright Top, we have these things up and running within a matter of moments so if there’s something that you missed please feel free to go back, log in and view this as many times as you’d like. On behalf of the CMO Council thank you so much for your time, thanks everyone.

 

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