Category Archives: Customer Acquisition & Retention
Arkady, you recently came back from the National Retail Federation conference. What are some of the issues that retailers are struggling with these days?
Arkady Kleyner: There are some interesting trends happening right now in retail. Amazon’s presence is creating a lot of disruption which is pushing traditional retailers to modernize their customer experience strategies. For example, most Brick and Mortar retailers have a web presence, but they’re realizing that web presence can’t just be a second arm to their business. To succeed, they need to integrate their web presence with their stores in a very intimate way. To make that happen, they really have to peel back the onion down to the fundamentals of how product data is shared and managed.
In the good old days, Brick and Mortar retailers could live with a somewhat disconnected product catalog, because they were always ultimately picking from physical goods. However in an integrated Web and Brick & Mortar environment, retailers must be far more accurate in their product catalog. The customers entire product selection process may happen on-line but then picked up at the store. So you can see where retailers need to be far more disciplined with their product data. This is really where a Product Information Management tool is critical, with so many SKUs to manage, retailers really need a process that makes sense from end to end for onboarding and communicating a product to the customer. And that is at the foundation of building an integrated customer experience.
In times of the digital customer, being online and connected always, we announced “commerce relevancy” as the next era of omnichannel and tailoring sales and marketing better to customers. What information are you seeing to be important when creating better customer shopping experience?
Arkady Kleyner:This is another paradigm in the integrated customer experience that retailers are trying to get their heads around. To appreciate how involved this is, just consider what a company like Amazon is doing. They have millions of customers and millions of products and thousands of partners. It’s literally a many to many to many relationship. And this is why Amazon is eating everybody alive. They know what products their customers like, they know how to reach those customers with those products, and they make it easy to buy it when you do. This isn’t something that Amazon created over night, but the requirements are no different for the rest of retailers. They need to ramp up the same type of capacity and reach. For example if I sell jewelry I may be selling it on my own company store but I may also have 5 other partnering sites including Amazon. Additionally, I may be using a dozen different advertising methods to drive demand. Now multiply that times the number of jewelry products I sell and you have a massive hairball of complexity. This is what we mean when we say that retailers need to be far more disciplined with their product data. Having a Product Information Management process that spans the onboarding of products all the way through to the digital communication of those products is critical to a retailer staying relevant.
In which businesses do you see the need for more efficient product catalog management and channel convergence?
Arkady Kleyner: There is a huge opportunity out there for the existing Brick & Mortar retailers that embrace an integrated customer experience. Amazon is not the de facto winner. We see a future where the store near you actually IS the online store. But to make that happen, Brick and Mortar retailers need to take a serious step back and treat their product data with the same reverence as they treat the product itself. This means a well-managed process for onboarding, de-duping, and categorizing their product catalog, because all the customer marketing efforts are ultimately an extension of that catalog.
Which performance indicators are important? How can retailers profit from it?
Arkady Kleyner: There are two layers of performance indicators that are important. The first is Operational Intelligence. This is the intelligence that determines what product should be shown to who. This is all based on customer profiling of purchase history. The second is Strategic Intelligence. This type of intelligence is the kind the helps you make overarching decisions on things like
-Maximizing the product margin by analyzing shipping and warehousing options
-Understanding product performance by demographics and regions
-Providing Flash Reports for Sales and Marketing
Which tools are needed to streamline product introduction but also achieve sales numbers?
Arkady Kleyner: Informatica is one of the few vendors that cares about data the same way retailers care about their products. So if you’re a retailer, you really need to treat your product data with the same reverence as your physical products then you need to consider leveraging Informatica as a partner. Their platform for managing product data is designed to encapsulate the entire process of onboarding, de-duping, categorizing, and syndicating product data. Additionally Informatica PIM provides a platform for managing all the digital media assets so Marketing teams are able to focus on the strategy rather than tactics. We’ve also worked with Informatica’s data integration products to bring the performance data from the Point of Sale systems for both Strategic and Tactical uses. On the tactical side we’ve used this to integrate inventories between Web and Brick & Mortar so customers can have an integrated experience. On the strategic side we’ve integrated Warehouse Management Systems with Labor Cost tracking systems to provide a 360 degree view of the product costing including shipping and storage to drive a higher per unit margins.
You can hear more from Arkady in our webinar “The Streamlined SKU: Using Analytics for Quick Product Introductions” on Tuesday, March 4, 2014.
Maybe the word “death” is a bit strong, so let’s say “demise” instead. Recently I read an article in the Harvard Business Review around how Big Data and Data Scientists will rule the world of the 21st century corporation and how they have to operate for maximum value. The thing I found rather disturbing was that it takes a PhD – probably a few of them – in a variety of math areas to give executives the necessary insight to make better decisions ranging from what product to develop next to who to sell it to and where.
Don’t get me wrong – this is mixed news for any enterprise software firm helping businesses locate, acquire, contextually link, understand and distribute high-quality data. The existence of such a high-value role validates product development but it also limits adoption. It is also great news that data has finally gathered the attention it deserves. But I am starting to ask myself why it always takes individuals with a “one-in-a-million” skill set to add value. What happened to the democratization of software? Why is the design starting point for enterprise software not always similar to B2C applications, like an iPhone app, i.e. simpler is better? Why is it always such a gradual “Cold War” evolution instead of a near-instant French Revolution?
Why do development environments for Big Data not accommodate limited or existing skills but always accommodate the most complex scenarios? Well, the answer could be that the first customers will be very large, very complex organizations with super complex problems, which they were unable to solve so far. If analytical apps have become a self-service proposition for business users, data integration should be as well. So why does access to a lot of fast moving and diverse data require scarce PIG or Cassandra developers to get the data into an analyzable shape and a PhD to query and interpret patterns?
I realize new technologies start with a foundation and as they spread supply will attempt to catch up to create an equilibrium. However, this is about a problem, which has existed for decades in many industries, such as the oil & gas, telecommunication, public and retail sector. Whenever I talk to architects and business leaders in these industries, they chuckle at “Big Data” and tell me “yes, we got that – and by the way, we have been dealing with this reality for a long time”. By now I would have expected that the skill (cost) side of turning data into a meaningful insight would have been driven down more significantly.
Informatica has made a tremendous push in this regard with its “Map Once, Deploy Anywhere” paradigm. I cannot wait to see what’s next – and I just saw something recently that got me very excited. Why you ask? Because at some point I would like to have at least a business-super user pummel terabytes of transaction and interaction data into an environment (Hadoop cluster, in memory DB…) and massage it so that his self-created dashboard gets him/her where (s)he needs to go. This should include concepts like; “where is the data I need for this insight?’, “what is missing and how do I get to that piece in the best way?”, “how do I want it to look to share it?” All that is required should be a semi-experienced knowledge of Excel and PowerPoint to get your hands on advanced Big Data analytics. Don’t you think? Do you believe that this role will disappear as quickly as it has surfaced?
I love exploring new places. I’ve had exceptional experiences at the W in Hong Kong, El Dorado Royale in the Riviera Maya and Ventana Inn in Big Sur. I belong to almost every loyalty program under the sun, but not all hospitality companies are capitalizing on the potential of my customer information. Imagine if employees had access to it so they could personalize their interactions with me and send me marketing offers that appeal to my interests.
Do I have high expectations? Yes. But so do many travelers. This puts pressure on marketing and sales executives who want to compete to win. According to Deloitte’s report, “Hospitality 2015: Game changers or spectators?,” hospitality companies need to adapt to meet consumers’ increasing expectations to know their preferences and tastes and to customize packages that suit individual needs.
In this interview, Jeff Klagenberg, senior principal at Myers-Holum, explains how one of the largest, most customer-focused companies in the hospitality industry is investing in better customer, product, and asset information. Why? To personalize customer interactions, bundle appealing promotion packages and personalize marketing offers across channels.
Q: What are the company’s goals?
A: The executive team at one of the world’s leading providers of family travel and leisure experiences is focused on achieving excellence in quality and guest services. They generate revenues from the sales of room nights at hotels, food and beverages, merchandise, admissions and vacation club properties. The executive team believes their future success depends on stronger execution based on better measurement and a better understanding of customers.
Q: What role does customer, product and asset information play in achieving these goals?
A: Without the highest quality business-critical data, how can employees continually improve customer interactions? How can they bundle appealing promotional packages or personalize marketing offers? How can they accurately measure the impact of sales and marketing efforts? The team recognized the powerful role of high quality information in their pursuit of excellence.
Q: What are they doing to improve the quality of this business-critical information?
A: To get the most value out of their data and deliver the highest quality information to business and analytical applications, they knew they needed to invest in an integrated information management infrastructure to support their data governance process. Now they use the Informatica Total Customer Relationship Solution, which combines data integration, data quality, and master data management (MDM). It pulls together fragmented customer information, product information, and asset information scattered across hundreds of applications in their global operations into one central, trusted location where it can be managed and shared with analytical and operational applications on an ongoing basis.
Q: How will this impact marketing and sales?
A: With clean, consistent and connected customer information, product information, and asset information in the company’s applications, they are optimizing marketing, sales and customer service processes. They get limitless insights into who their customers are and their valuable relationships, including households, corporate hierarchies and influencer networks. They see which products and services customers have purchased in the past, their preferences and tastes. High quality information enables the marketing and sales team to personalize customer interactions across touch points, bundle appealing promotional packages, and personalize marketing offers across channels. They have a better understanding of which marketing, advertising and promotional programs work and which don’t.
Q: What is the role did the marketing and sales leaders play in this initiative?
A: The marketing leaders and sales leaders played a key role in getting this initiative off the ground. With an integrated information management infrastructure in place, they’ll benefit from better integration between business-critical master data about customers, products and assets and transaction data.
Q. How will this help them gain customer insights from “Big Data”?
A. We helped the business leaders understand that getting customer insights from “Big Data” such as weblogs, call logs, social and mobile data requires a strong backbone of integrated business-critical data. By investing in a data-centric approach, they future-proofed their business. They are ready to incorporate any type of data they will want to analyze, such as interaction data. A key realization was there is no such thing as “Small Data.” The future is about getting very bit of understanding out of every data source.
Q: What advice do you have for hospitality industry executives?
A: Ask yourself, “Which of our strategic initiatives can be achieved with inaccurate, inconsistent and disconnected information?” Most executives know that the business-critical data in their applications, used by employees across the globe, is not the highest quality. But they are shocked to learn how much this is costing the company. My advice is talk to IT about the current state of your customer, product and asset information. Find out if it is holding you back from achieving your strategic initiatives.
Also, many business executives are excited about the prospect of analyzing “Big Data” to gain revenue-generating insights about customers. But the business-critical data about customers, products and assets is often in terrible shape. To use an analogy: look at a wheat field and imagine the bread it will yield. But don’t forget if you don’t separate the grain from the chaff you’ll be disappointed with the outcome. If you are working on a Big Data initiative, don’t forget to invest in the integrated information management infrastructure required to give you the clean, consistent and connected information you need to achieve great things.
“If you don’t like change, you’re going to like irrelevancy a lot less.” I saw this powerful Ralph Waldo Emerson quotation in an MDM Summit presentation by Dagmar Garcia, senior manager of marketing data management at Citrix. In this interview, Dagmar explains how Citrix is achieving a measurable impact on marketing results by improving the quality of customer information and prospect information.
Q: What is Citrix’s mission?
A: Citrix is a $2.6 billion company. We help people work and collaborate from anywhere by easily accessing enterprise applications and data from any device. More than 250,000 organizations around the globe use our solutions and we have over 10,000 partners in 100 countries who resell Citrix solutions.
Q: What are marketing’s goals?
A: We operate in a hyper-competitive market. It’s critical to retain and expand relationships with existing enterprise and SMB customers and attract new ones. The marketing team’s goals are to boost campaign effectiveness and lead-to-opportunity conversion rates, while improving operational efficiencies.
But, it’s difficult to create meaningful customer segments and target them with relevant cross-sell and up-sell offers if marketing lacks access to clean, consistent and connected customer information and visibility into the total customer relationship across product lines.
Q: What is your role in achieving these goals?
A: I’ve been responsible for global marketing data management at Citrix for six years. My role is to identify, implement and maintain technical and business data management processes.I work with marketing leadership, GEO-based team members, sales operations, and operational experts to understand requirements, develop solutions and communicate results. I strive to create innovative solutions to improve the quality of master data at Citrix, including the roll-out and successful adoption of data governance and stewardship practices within Marketing and across other departments.
Q: What drove the decision to tackle inaccurate, inconsistent and disconnected customer and prospect information?
A: In 2011, the quality of customer information and prospect information was identified as the #1 problem by our sales and marketing teams. Account and contact information was incomplete, inaccurate and duplicated in our CRM system.
Another challenge was fragmented and inconsistent master account information scattered across the organization’s multiple applications. It was difficult to know which source had the most accurate and up-to-date customer and prospect information.
To be successful, we needed a single source of the truth, one system of reference where data management best practices were centralized and consistent. This was a requirement to understand the total customer relationship across product lines. We asked ourselves:
- How can we improve campaign effectiveness if more than 40% of the contacts in our customer relationship management system (CRM) are inactive?
- How can we create meaningful customer segments for targeted cross-sell and up-sell offers when we don’t have visibility into all the products they already have?
- How can we improve lead to opportunity conversion rates if we have incomplete prospect data?
- How can we improve operational efficiencies if we have double the duplicate customer and prospect information than the industry standard?
- How can we maintain high data quality standards in our global operations if we lack the data quality technology and processes needed to be successful?
Q: How are you managing customer and prospect information now?
A: We built a marketing data management foundation. We centralized our data management and reduced manual, error-prone and time-consuming data quality efforts. To decrease the duplicate account and contact rate, we focused on managing the quality of our data as close to the source as possible by improving data validation at points of entry.
Q: What role does Informatica play?
A: We using master data management (MDM) to:
- pull together fragmented customer, prospect and partner information scattered across applications into one central, trusted location where it can be mastered, managed and shared on an ongoing basis,
- organize customer, prospect and partner information so we know how companies and people are related to each other, which hierarchies and networks they belong to, including their roles and organizations, and
- syndicate clean, consistent and connected customer, partner and product information to applications, such as CRM and data warehouses for analytics.
Q: Why did you choose Informatica?
A: After completing a thorough analysis of our gaps, we knew the best solution was a combination of MDM technology and a data governance process. We wanted to empower the business to manage customer information, navigate multiple hierarchies, handle exceptions and make changes with a transparent process through an easy-to-use interface.
At the same time, we did extensive industry research and learned Informatica MDM was ranked as a visionary and thought leader in the master data management solution space and could support our data governance process.
Q: Can you share some of the results you’ve achieved?
A: Now that marketing uses clean, consistent and connected customer and prospect information and an understanding of the total customer relationship, we’ve seen a positive impact on these key metrics:
↑ 20% lead-to-opportunity conversion rates
↑ 20% operational efficiency
↑ 50% quality data at point of entry
↓ 50% in prospect accounts duplication rate
↓ 50% in creation of duplicate prospect accounts and contacts
↓ 50% in junk data rate
Murphy’s First Law of Bad Data – If You Make A Small Change Without Involving Your Client – You Will Waste Heaps Of Money
I have not used my personal encounter with bad data management for over a year but a couple of weeks ago I was compelled to revive it. Why you ask? Well, a complete stranger started to receive one of my friend’s text messages – including mine – and it took days for him to detect it and a week later nobody at this North American wireless operator had been able to fix it. This coincided with a meeting I had with a European telco’s enterprise architecture team. There was no better way to illustrate to them how a customer reacts and the risk to their operations, when communication breaks down due to just one tiny thing changing – say, his address (or in the SMS case, some random SIM mapping – another type of address).
In my case, I moved about 250 miles within the United States a couple of years ago and this seemingly common experience triggered a plethora of communication screw ups across every merchant a residential household engages with frequently, e.g. your bank, your insurer, your wireless carrier, your average retail clothing store, etc.
For more than two full years after my move to a new state, the following things continued to pop up on a monthly basis due to my incorrect customer data:
- In case of my old satellite TV provider they got to me (correct person) but with a misspelled last name at my correct, new address.
- My bank put me in a bit of a pickle as they sent “important tax documentation”, which I did not want to open as my new tenants’ names (in the house I just vacated) was on the letter but with my new home’s address.
- My mortgage lender sends me a refinancing offer to my new address (right person & right address) but with my wife’s as well as my name completely butchered.
- My wife’s airline, where she enjoys the highest level of frequent flyer status, continually mails her offers duplicating her last name as her first name.
- A high-end furniture retailer sends two 100-page glossy catalogs probably costing $80 each to our address – one for me, one for her.
- A national health insurer sends “sensitive health information” (disclosed on envelope) to my new residence’s address but for the prior owner.
- My legacy operator turns on the wrong premium channels on half my set-top boxes.
- The same operator sends me a SMS the next day thanking me for switching to electronic billing as part of my move, which I did not sign up for, followed by payment notices (as I did not get my invoice in the mail). When I called this error out for the next three months by calling their contact center and indicating how much revenue I generate for them across all services, they counter with “sorry, we don’t have access to the wireless account data”, “you will see it change on the next bill cycle” and “you show as paper billing in our system today”.
Ignoring the potential for data privacy law suits, you start wondering how long you have to be a customer and how much money you need to spend with a merchant (and they need to waste) for them to take changes to your data more seriously. And this are not even merchants to whom I am brand new – these guys have known me and taken my money for years!
One thing I nearly forgot…these mailings all happened at least once a month on average, sometimes twice over 2 years. If I do some pigeon math here, I would have estimated the postage and production cost alone to run in the hundreds of dollars.
However, the most egregious trespass though belonged to my home owner’s insurance carrier (HOI), who was also my mortgage broker. They had a double whammy in store for me. First, I received a cancellation notice from the HOI for my old residence indicating they had cancelled my policy as the last payment was not received and that any claims will be denied as a consequence. Then, my new residence’s HOI advised they added my old home’s HOI to my account.
After wondering what I could have possibly done to trigger this, I called all four parties (not three as the mortgage firm did not share data with the insurance broker side – surprise, surprise) to find out what had happened.
It turns out that I had to explain and prove to all of them how one party’s data change during my move erroneously exposed me to liability. It felt like the old days, when seedy telco sales people needed only your name and phone number and associate it with some sort of promotion (back of a raffle card to win a new car), you never took part in, to switch your long distance carrier and present you with a $400 bill the coming month. Yes, that also happened to me…many years ago. Here again, the consumer had to do all the legwork when someone (not an automatic process!) switched some entry without any oversight or review triggering hours of wasted effort on their and my side.
We can argue all day long if these screw ups are due to bad processes or bad data, but in all reality, even processes are triggered from some sort of underlying event, which is something as mundane as a database field’s flag being updated when your last purchase puts you in a new marketing segment.
Now imagine you get married and you wife changes her name. With all these company internal (CRM, Billing, ERP), free public (property tax), commercial (credit bureaus, mailing lists) and social media data sources out there, you would think such everyday changes could get picked up quicker and automatically. If not automatically, then should there not be some sort of trigger to kick off a “governance” process; something along the lines of “email/call the customer if attribute X has changed” or “please log into your account and update your information – we heard you moved”. If American Express was able to detect ten years ago that someone purchased $500 worth of product with your credit card at a gas station or some lingerie website, known for fraudulent activity, why not your bank or insurer, who know even more about you? And yes, that happened to me as well.
Tell me about one of your “data-driven” horror scenarios?
I recently had a lengthy conversation with a business executive of a European telco. His biggest concern was to not only understand the motivations and related characteristics of consumers but to accomplish this insight much faster than before. Given available resources and current priorities this is something unattainable for many operators.
Unlike a few years ago – remember the time before iPad – his organization today is awash with data points from millions of devices, hundreds of device types and many applications.
One way for him to understand consumer motivation; and therefore intentions, is to get a better view of a user’s network and all related interactions and transactions. This includes his family household, friends and business network (also a type of household). The purpose of householding is to capture social and commercial relationships in a grouping of individuals (or businesses or both mixed together) in order to identify patterns (context), which can be exploited to better serve a customer a new individual product or bundle upsell, to push relevant apps, audio and video content.
Let’s add another layer of complexity by understanding not only who a subscriber is, who he knows and how often he interacts with these contacts and the services he has access to via one or more devices but also where he physically is at the moment he interacts. You may also combine this with customer service and (summarized) network performance data to understand who is high-value, high-overhead and/or high in customer experience. Most importantly, you will also be able to assess who will do what next and why.
Some of you may be thinking “Oh gosh, the next NSA program in the making”. Well, it may sound like it but the reality is that this data is out there today, available and interpretable if cleaned up, structured and linked and served in real time. Not only do data quality, ETL, analytical and master data systems provide the data backbone for this reality but process-based systems dealing with the systematic real-time engagement of consumers are the tool to make it actionable. If you add some sort of privacy rules using database or application-level masking technologies, most of us would feel more comfortable about this proposition.
This may feel like a massive project but as many things in IT life; it depends on how you scope it. I am a big fan of incremental mastering of increasingly more attributes of certain customer segments, business units, geographies, where lessons learnt can be replicated over and over to scale. Moreover, I am a big fan of figuring out what you are trying to achieve before even attempting to tackle it.
The beauty behind a “small” data backbone – more about “small data” in a future post – is that if a certain concept does not pan out in terms of effort or result, you have just wasted a small pile of cash instead of the $2 million for a complete throw-away. For example: if you initially decided that the central lynch pin in your household hub & spoke is the person, who owns the most contracts with you rather than the person who pays the bills every month or who has the largest average monthly bill, moving to an alternative perspective does not impact all services, all departments and all clients. Nevertheless, the role of each user in the network must be defined over time to achieve context, i.e. who is a contract signee, who is a payer, who is a user, who is an influencer, who is an employer, etc.
Why is this important to a business? It is because without the knowledge of who consumes, who pays for and who influences the purchase/change of a service/product, how can one create the right offers and target them to the right individual.
However, in order to make this initial call about household definition and scope or look at the options available and sensible, you have to look at social and cultural conventions, what you are trying to accomplish commercially and your current data set’s ability to achieve anything without a massive enrichment program. A couple of years ago, at a Middle Eastern operator, it was very clear that the local patriarchal society dictated that the center of this hub and spoke model was the oldest, non-retired male in the household, as all contracts down to children of cousins would typically run under his name. The goal was to capture extended family relationships more accurately and completely in order to create and sell new family-type bundles for greater market penetration and maximize usage given new bandwidth capacity.
As a parallel track aside from further rollout to other departments, customer segments and geos, you may also want to start thinking like another European operator I engaged a couple of years ago. They were trying to outsource some data validation and enrichment to their subscribers, which allowed for a more accurate and timely capture of changes, often life-style changes (moves, marriages, new job). The operator could then offer new bundles and roaming upsells. As a side effect, it also created a sense of empowerment and engagement in the client base.
I see bits and pieces of some of this being used when I switch on my home communication systems running broadband signal through my X-Box or set-top box into my TV using Netflix and Hulu and gaming. Moreover, a US cable operator actively promotes a “moving” package to help make sure you do not miss a single minute of entertainment when relocating.
Every time now I switch on my TV, I get content suggested to me. If telecommunication services would now be a bit more competitive in the US (an odd thing to say in every respect) and prices would come down to European levels, I would actually take advantage of the offer. And then there is the log-on pop up asking me to subscribe (or throubleshoot) a channel I have already subscribed to. Wonder who or what automated process switched that flag.
Ultimately, there cannot be a good customer experience without understanding customer intentions. I would love to hear stories from other practitioners on what they have seen in such respect
As I continue to counsel insurers about master data, they all agree immediately that it is something they need to get their hands around fast. If you ask participants in a workshop at any carrier; no matter if life, p&c, health or excess, they all raise their hands when I ask, “Do you have broadband bundle at home for internet, voice and TV as well as wireless voice and data?”, followed by “Would you want your company to be the insurance version of this?”
Now let me be clear; while communication service providers offer very sophisticated bundles, they are also still grappling with a comprehensive view of a client across all services (data, voice, text, residential, business, international, TV, mobile, etc.) each of their touch points (website, call center, local store). They are also miles away of including any sort of meaningful network data (jitter, dropped calls, failed call setups, etc.)
Similarly, my insurance investigations typically touch most of the frontline consumer (business and personal) contact points including agencies, marketing (incl. CEM & VOC) and the service center. On all these we typically see a significant lack of productivity given that policy, billing, payments and claims systems are service line specific, while supporting functions from developing leads and underwriting to claims adjucation often handle more than one type of claim.
This lack of performance is worsened even more by the fact that campaigns have sub-optimal campaign response and conversion rates. As touchpoint-enabling CRM applications also suffer from a lack of complete or consistent contact preference information, interactions may violate local privacy regulations. In addition, service centers may capture leads only to log them into a black box AS400 policy system to disappear.
Here again we often hear that the fix could just happen by scrubbing data before it goes into the data warehouse. However, the data typically does not sync back to the source systems so any interaction with a client via chat, phone or face-to-face will not have real time, accurate information to execute a flawless transaction.
On the insurance IT side we also see enormous overhead; from scrubbing every database from source via staging to the analytical reporting environment every month or quarter to one-off clean up projects for the next acquired book-of-business. For a mid-sized, regional carrier (ca. $6B net premiums written) we find an average of $13.1 million in annual benefits from a central customer hub. This figure results in a ROI of between 600-900% depending on requirement complexity, distribution model, IT infrastructure and service lines. This number includes some baseline revenue improvements, productivity gains and cost avoidance as well as reduction.
On the health insurance side, my clients have complained about regional data sources contributing incomplete (often driven by local process & law) and incorrect data (name, address, etc.) to untrusted reports from membership, claims and sales data warehouses. This makes budgeting of such items like medical advice lines staffed by nurses, sales compensation planning and even identifying high-risk members (now driven by the Affordable Care Act) a true mission impossible, which makes the life of the pricing teams challenging.
Over in the life insurers category, whole and universal life plans now encounter a situation where high value clients first faced lower than expected yields due to the low interest rate environment on top of front-loaded fees as well as the front loading of the cost of the term component. Now, as bonds are forecast to decrease in value in the near future, publicly traded carriers will likely be forced to sell bonds before maturity to make good on term life commitments and whole life minimum yield commitments to keep policies in force.
This means that insurers need a full profile of clients as they experience life changes like a move, loss of job, a promotion or birth. Such changes require the proper mitigation strategy, which can be employed to protect a baseline of coverage in order to maintain or improve the premium. This can range from splitting term from whole life to using managed investment portfolio yields to temporarily pad premium shortfalls.
Overall, without a true, timely and complete picture of a client and his/her personal and professional relationships over time and what strategies were presented, considered appealing and ultimately put in force, how will margins improve? Surely, social media data can help here but it should be a second step after mastering what is available in-house already. What are some of your experiences how carriers have tried to collect and use core customer data?
Recommendations and illustrations contained in this post are estimates only and are based entirely upon information provided by the prospective customer and on our observations. While we believe our recommendations and estimates to be sound, the degree of success achieved by the prospective customer is dependent upon a variety of factors, many of which are not under Informatica’s control and nothing in this post shall be relied upon as representative of the degree of success that may, in fact, be realized and no warrantee or representation of success, either express or implied, is made.
I had a disturbing conversation at Dreamforce. Long story short, thousands of highly skilled and highly paid financial advisors (read sales reps) at a large financial services company are spending most of their day pulling together information about their clients in a spreadsheet, leaving only a few hours to engage with clients and generate revenue.
Not all valuable customer information is in Salesforce
Why? They don’t have a 360-degree customer view within Salesforce.
Why not? Not all client information that’s valuable to the financial advisors is in Salesforce. Important client information is in other applications too, such as:
- Marketing automation application
- Customer support application
- Account management applications
- Finance applications
- Business intelligence applications
Are you in sales? Do you work for a company that has multiple products or lines of business? Then you can probably relate. In my 15 years of experience working with sales, I’ve found this to be a harsh reality. You have to manually pull together customer information, which is a time-consuming process that doesn’t boost job satisfaction.
Stop building 360-degree customer views in spreadsheets
So what can you do about it? Stop building 360-degree customer views in spreadsheets. There is a better way and your sales operations leader can help.
One of my favorite customer success stories is about one of the world’s leading wealth management companies, with 16,000 financial advisors globally. Like most companies, their goal is to increase revenue by understanding their customers’ needs and making relevant cross-sell and up-sell offers.
But, the financial advisors needed an up-to-date view of the “total customer relationship” with the bank before they talked to their high net-worth clients. They wanted to appear knowledgeable and offer a product the client might actually want.
Can you guess what was holding them back? The bank operated in an account-centric world. Each line of business had its own account management application. To get a 360-degree customer view, the financial advisors spent 70% of their time pulling important client information from different applications into spreadsheets. Sound familiar?
Once the head of sales realized this, he decided to invest in information management technology that provides clean, consistent and connected customer information and delivers a 360-degree customer view within Salesforce.
The result? They’ve had a $50 million dollar impact annually and a 30% increase in productivity. In fact, word spread to other banks and the 360-degree customer view in Salesforce became an incentive to attract top talent in the industry.
Ask sales operations to give you 360-degree customer views within Salesforce
I urge you to take action. In particular, talk to your sales operations leader if he or she is at all interested in improving performance and productivity, acquiring and retaining top sales talent, and cutting costs.
Want to see how you can get 360-degree customer views in Salesforce? Check out this demo: Enrich Customer Data in Your CRM Application with MDM. Then schedule a meeting with your sales operations leader.
Have a similar experience to share? Please share it in the comments below.
I believe that most in the software business believe that it is tough enough to calculate and hence financially justify the purchase or build of an application - especially middleware – to a business leader or even a CIO. Most of business-centric IT initiatives involve improving processes (order, billing, service) and visualization (scorecarding, trending) for end users to be more efficient in engaging accounts. Some of these have actually migrated to targeting improvements towards customers rather than their logical placeholders like accounts. Similar strides have been made in the realm of other party-type (vendor, employee) as well as product data. They also tackle analyzing larger or smaller data sets and providing a visual set of clues on how to interpret historical or predictive trends on orders, bills, usage, clicks, conversions, etc.
If you think this is a tough enough proposition in itself, imagine the challenge of quantifying the financial benefit derived from understanding where your “hardware” is physically located, how it is configured, who maintained it, when and how. Depending on the business model you may even have to figure out who built it or owns it. All of this has bottom-line effects on how, who and when expenses are paid and revenues get realized and recognized. And then there is the added complication that these dimensions of hardware are often fairly dynamic as they can also change ownership and/or physical location and hence, tax treatment, insurance risk, etc.
Such hardware could be a pump, a valve, a compressor, a substation, a cell tower, a truck or components within these assets. Over time, with new technologies and acquisitions coming about, the systems that plan for, install and maintain these assets become very departmentalized in terms of scope and specialized in terms of function. The same application that designs an asset for department A or region B, is not the same as the one accounting for its value, which is not the same as the one reading its operational status, which is not the one scheduling maintenance, which is not the same as the one billing for any repairs or replacement. The same folks who said the Data Warehouse is the “Golden Copy” now say the “new ERP system” is the new central source for everything. Practitioners know that this is either naiveté or maliciousness. And then there are manual adjustments….
Moreover, to truly take squeeze value out of these assets being installed and upgraded, the massive amounts of data they generate in a myriad of formats and intervals need to be understood, moved, formatted, fixed, interpreted at the right time and stored for future use in a cost-sensitive, easy-to-access and contextual meaningful way.
I wish I could tell you one application does it all but the unsurprising reality is that it takes a concoction of multiple. None or very few asset life cycle-supporting legacy applications will be retired as they often house data in formats commensurate with the age of the assets they were built for. It makes little financial sense to shut down these systems in a big bang approach but rather migrate region after region and process after process to the new system. After all, some of the assets have been in service for 50 or more years and the institutional knowledge tied to them is becoming nearly as old. Also, it is probably easier to engage in often required manual data fixes (hopefully only outliers) bit-by-bit, especially to accommodate imminent audits.
So what do you do in the meantime until all the relevant data is in a single system to get an enterprise-level way to fix your asset tower of Babel and leverage the data volume rather than treat it like an unwanted step child? Most companies, which operate in asset, fixed-cost heavy business models do not want to create a disruption but a steady tuning effect (squeezing the data orange), something rather unsexy in this internet day and age. This is especially true in “older” industries where data is still considered a necessary evil, not an opportunity ready to exploit. Fact is though; that in order to improve the bottom line, we better get going, even if it is with baby steps.
If you are aware of business models and their difficulties to leverage data, write to me. If you even know about an annoying, peculiar or esoteric data “domain”, which does not lend itself to be easily leveraged, share your thoughts. Next time, I will share some examples on how certain industries try to work in this environment, what they envision and how they go about getting there.