Data Integration is the New Technology Marketing Game Changer: Interview with Ashley Stirrup

Interviewer: Today I am very pleased to welcome Ashley Stirrup, Chief Marketing Officer of Talend. Ashley is responsible for driving market leadership, global awareness, product management and demand gen. So, how does Talend describe themselves? They say that their mission is to help connect the data driven enterprise. So, Talend is an open source provider of data integration software with over 1800 customers. Ashley welcome.

Ashley: Thank you, glad to be here.

Interviewer: Last time we spoke we spoke about how a marketer’s strategy or a company’s marketing strategy should and could change now that they have data available to them. I’d love to hear some of your thoughts on that topic.
Ashley: Yeah, and as you said, Talend is in the data integration space, a really hot area for us is around big data and most notably Hadoop and also does SQL databases. These are new technologies that allow companies to analyze data that they never could have done before. We really see that falling into a couple of different categories. One is analyzing data they already had that was just too voluminous to really access. The other is accessing totally new types of data. One example of the first category is Lenovo. As you know, a very well-known hardware company, very strong in laptops.

Interviewer: Know them well.
Ashley: Yeah, and as you said, Talend is in the data integration space, a really hot area for us is around big data and most notably Hadoop and also does SQL databases. These are new technologies that allow companies to analyze data that they never could have done before. We really see that falling into a couple of different categories. One is analyzing data they already had that was just too voluminous to really access. The other is accessing totally new types of data. One example of the first category is Lenovo. As you know, a very well-known hardware company, very strong in laptops.

Interviewer: Know them well.

Ashley: Yeah, and they are using our tools to pull data together from a whole variety of different data sources inside their company to really give them a more complete view of their customers than they ever had before. What that is allowing them to do is create more finely grained target segments of customers, really do much more tailored marketing campaigns too.

Interviewer: Right, right interesting. Yes, in fact the CMO of Lenovo, David Roman is featured in my book which is coming out next year, also called Moneyball for Marketing, so interesting connection there. I didn’t know we had that.

Ashley: Great yeah.

Interviewer: So, tell us more about that fine tuning of the understanding of the target and what he do with that. How do you get there? How do you fine tune the understanding of who you customer is with the data?

Ashley: It really varies from company to company and I can’t go into the specifics with Lenovo. But, one example of something that we’re seeing companies do that kind of falls into the accessing new data sources is analyzing social data and then finding ways of linking that to existing information they have within their customer data so that they can see who is actually happy with their products. Who’s tweeting out positive information and who’s tweeting out negative information for example. So, they’re not only looking at trends in the overall reaction to products in marketing campaigns and things like that, but they’re also able to use it to do really tailored marketing campaigns. How should we be marketing that are happy with our products? What else can we sell to the people that are happy with our products? Things like that.

Interviewer: So, do you get down to the individual level so I know that this individual is tweeting and saying these things therefore, when they come to my website I’m going to treat them differently?

Ashley: We definitely have some customers that are doing it. It’s absolutely not the norm yet for sure. It’s on the cutting edge. But, some of our credit card, financial service customers, are in fact doing it.

Interviewer: Really. Wow. That’s really powerful and it raises the question many consumers ask which is do I want my brand doing that for me. Can you talk a little bit about how brands might overcome that in terms of creating permission and engagement at the level where the consumer actually wants you to notice what they’re doing?

Ashley: Yeah, you know that’s a really interesting topic and I certainly wouldn’t consider myself an expert on it. What I would say is that – how many times have we all called up a particular vendor that is servicing us and been frustrated that they didn’t know more about us? For sure it starts with the information they ought to know, which is what you bought last; what your last customer service incident was, things like that. But, if they can see you using that information to provide better service or to provide a more tailored offering to them they are going to respond positively to it.

Interviewer: Of course, I suppose a simple example would be – I think you told me a story about a group of doctors and if I had to go to a different office and they had me fill in my home address against I’d get pretty frustrated with that.

Ashley: Yeah, yeah that’s a great example.

Interviewer: Good, so let’s talk about big data. I just used kind of a small data example, but share with us how some of the big brands are leveraging really big data they have when they have a lot of products, they have a lot of customers, they have a lot of advertising and a lot of touch points. How are they bringing things together to market more effectively?

Ashley: Yeah well one example which is a single channel, it’s about the web, but it’s about using data in a different way. We have a hardware company in the UK where they had a strategy that they recognized that there are only so many SKUs, so many products they could be carrying in their stores but they were the long [00:07:00 – Indecipherable] of demand for things that their suppliers could offer. So they turned to the web to build an extended online catalog. They now are offering over 5 million different products at that online site. And the only way they were able to do it was by making it self-service for all their suppliers. So their suppliers could upload information from their product catalogs. The challenge was that in doing that they found that some suppliers were much better at it than others.

Interviewer: Right.

Ashley: They really needed to take what I call a data-driven approach to get into a high quality online catalog. So, the first thing was just ensuring that when people uploaded information they were providing information in all the right categories, all the right fields were filled in. And that they were only uploading products once. They did a lot of work around scoring all the information that each supplier was uploading to make sure that they were meeting those standards and enforcing that there were no duplicates and things like that. Then over time they started looking at how many refused does each one of these different products have and giving the suppliers scorecards for which of their products – not only did they have descriptions, but they had rich descriptions and they were seeing uptake in purchase and even increase number of refused. So, they were using all those tools to drive a better and better experience with this online website.

Interviewer: And I suppose that’s good for the consumer too because as you collect information about a particular SKU I can see that back to the consumer. They can make better decisions. They can find what they need probably more easily.

Ashley: Absolutely yeah, because there were more things they could search on. There were forcing better descriptions of the products. All that ultimately led to a better customer experience. You’re absolutely right.

Interviewer: And that drives the suppliers to provide higher-quality information because it’s going to help sell more of their product. Interesting.

Ashley: Yeah yeah, well not only that, but our customer was using that information to personally drive those suppliers. So not only was it in the supplier’s best interest, but they had their customers saying to them this information is got to be done.

Interviewer: Excellent, excellent. Let’s talk a little bit about multichannel when you have a website you have twitter, you have mobile where maybe they are looking at you on email or on a third-party website. Can you talk about how companies are able to collect that data and use it to be smarter about who they are marketing to?

Ashley: Yeah, the customer I was thinking of it is again a little more specific than that. So, this is one of the largest online retailers in Germany.

Interviewer: Okay.

Ashley: What they are doing, not only is there these new technologies for Hadoop and NoSQL will allow you to analyze much larger volumes of data, but as Hadoop is maturing there is more and more real time capabilities that go along with it.

Interviewer: Yeah.

Ashley: What they are doing is they’ve been able to use this information to use predictive analytics to look at customers’ behavior online and actually predict when a customer is likely to abandon a shopping cart. You know, we all do that. We go online, we enter a number of things into the shopping cart and then somebody comes through the door kids got a get to soccer practice or what have you, and you leave the cart. They’ve gotten so they found they are able to predict, with 90% accuracy, when somebody is likely to abandon the cart, and then they are driving last-minute offers. They actually call it last defense – to pop up and offer to say hey, don’t go yet, here’s an extra 10% go ahead and complete this transaction.

Interviewer: Oh wow, I want to know where that website is so I can game the system right.

Ashley: Right, you want to be in the 10% category.

Interviewer: That’s right. Well also I would think there is a lot to learn about the shopping experience too because it’s not always because I have a soccer game to go to but maybe I’m confused at how the shopping experience works.

Ashley: Yeah.

Interviewer: I would imagine they could learn a lot by tracking my behavior.

Ashley: Yeah, well actually that same company has a separate project where they are doing a lot of work around segmenting their customers to understand what the different profiles of buyers they have and how to optimize the experience for each of those things.

Interviewer: That’s interesting, so they have data about the type of customer, or maybe even down to who it is at the individual level, but they also have data about my experience right?

Ashley: Yeah.

Interviewer: What am I doing on the site and how do I tie those two together which enables me to predict behavior which means I can serve them better. That’s really powerful.

Ashley: Yeah, yeah absolutely, combining all that with past purchase information, exactly.

Interviewer: Excellent, so what other things do you see happening with big data for marketers? What are some other cutting edge examples that we can talk about?

Ashley: Well another example, you alluded to it actually, in the medical industry where there is this alliance of healthcare providers. It is targeted at serving the elderly and helping them make the best use of Medicare and Medicaid by using a network of providers to get the absolute right service based on their individual needs. The challenge in that particular case is just how do you have all of these different providers create the feeling of one experience across the customer base. You mentioned that concept of every time you go to the doctor don’t want to have to fill out all the forms and provide all your medical information.

Interviewer: Right, right.

Ashley: Investing in tools that allow a loosely coupled group of the organizations to share information; have a centralized view of their shared customers and be able to share information and provide better service. And have all that information on those patients is a great example of how we are seeing companies recognize that being data-driven isn’t just about being data-driven within their four walls but how do they include their suppliers how do they include their partners within that as well.

Interviewer: Right, right, okay good. Alright I have two more questions for you. One is going to be a technical question. Actually it’s going to be helping our listeners understand a technical issue so that we don’t have to think too technically, and the second is going to be about the future. I want to go back to – you mentioned a couple of times Hadoop and NoSQL and I’m going to assume a lot of listeners don’t really know what those are. So, from a marketer’s perspective what should we need to understand about Hadoop and NoSQL? How are they relevant to us as marketers?

Ashley: Well I say the single biggest thing is it’s a new type of database, database platform that allows you to analyze far larger sets of data than ever before at dramatically reduced prices. The cost is 1/30th to 1/50th of what people are spending on traditional enterprise data warehouses.

Interviewer: Interesting.

Ashley: So, it really opens up the possibility of analyzing far more data than anybody has done before. There is a lot of examples of people, financial services is a great example of this, where they are backing up their historical customer information to tapes so that if an incident ever comes up they can go pull that tape out of storage and access that information. And so, before it was basically trapped information. You had it in some warehouse somewhere on tape but it wasn’t accessible to anybody. Now that information can be what they call live archives. It’s actually in Hadoop so it is accessible right away. It allows you to do all these additional analytic things as well as have it be a backup in case a customer has a complaint about a past transaction or something like that.

Interviewer: Very interesting. I actually have an additional question now that you’ve explained that a little bit, and that he is in most marketing organizations they have not sat down with IT to say let’s talk about our data architecture from the standpoint of what our demands are because we as marketers have specific needs as it relates to marketing. And yet, I see that that is an important step that marketers need to take. They need to be at the table when the design is happening for that data warehouse or for that data infrastructure that is being pulled together, because absent that the IT organization is just going to build a great whatever it is they’re going to build. But marketers need to say here is the purpose for that. Here is how I need to get access to that data or what I want to do with it. Tell me if you’re seeing that happen or not. Are marketers figuring out that they really need to be communicating in a different way now about data integration?

Ashley: I think the best marketers are, but it’s still an area where it’s a lot of room for growth. It’s interesting you say that because having worked in the software industry for a long time I spend a lot of time with good software engineers and one of the things I’ve always admired about them is they wouldn’t just say okay what are the requirements you ask for today, but where are you going and where do you need to be next and what do you need to do after that.

Interviewer: Right.

Ashley: A great example, a tangible example of how that would apply to marketing is there are all these great cloud-based services applications that are out they are today that marketing often will get really excited about and they’ll go buy two, three, four, five of these things and then suddenly one day they’ll turn around and go, oh IT I need you to pull all the data together across these five [00:17:35 – Indecipherable].

Interviewer: Right, right, right.

Ashley: IT will be like; oh you actually bought five new apps that I didn’t even know about.

Interviewer: Right.

Ashley: And so there will be a huge gulch between expectations of the business and the ability for IT to deliver it. And so, thinking about that long-term roadmap and sitting down with IT and mapping it out, particularly if you’re in an organization that has a lot of data. You can get three to four times the return on your IT investment if you’re thinking about that in terms of a roadmap and not just what I need to do next quarter, or what I need to do for this next campaign.

Interviewer: Will that’s great. We know one company, Domino’s pizza, that really declared to his CMO, or the CEO I should say, declared to the CMO and the CIO thou shalt work together because we are going to be a data-driven company and I need the two of you to be in the same room all the time because of this very issue you’re talking about. Alright last question for you. Tell us a little bit about the future as it relates to big data. What do you see happening in the next year or so?

Ashley: Yeah well I think there are two major trends that I talk about in the data space in general. So, for sure with Hadoop and big data I’d say the single biggest trend is real time. How to do more and more things real time? How can you affect what somebody saying on the phone with the customer or on the web with an experience? The second thing is cloud applications integration tools in the cloud. I think you’re going to see a whole another wave of tools that are going to be much more accessible, not to the CMO, but to the marketing analysts, the marketing operations type person that gives them more power and control, allows them to collaborate more with IT. I believe it’s going to give people more tools that they can access data faster and be more flexible about how they do analytics. It’s going to allow them to use data in new ways and just be much more agile.

Interviewer: And that ties in, they are connected right, because that ties in to my real time capability.

Ashley: Yeah absolutely. Real time and just getting more insight out of the data that you already have. So often you see people pouring a whole bunch of information into a data warehouse but only a small sliver of it actually really gets analyzed in depth. But you can put more of that control into the marketing analysts hands so they can say this is exactly how I want the data to look Mr. IT. I’ve actually pulled out a subset of the data and modeled it exactly right. Now, here is the model. Can you go build me the data integration jobs that’ll actually
get me the full data set around this [00:20:35 Indecipherable]?

Interviewer: Very good. Well thank you very much for sharing that with us Ashley. I appreciate your insights and some of the stories you told about what companies can do to be smarter about leveraging big data and I hope a lot of people listening will want to learn more about how to do this so they can be smarter marketers, so thank you once again.

Ashley: Thank you my pleasure.

Interviewer: All right, talk to you soon.

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