Category Archives: Real-Time
Recently, I presented a Business Value Assessment to a client. The findings were based on a revenue-generating state government agency. Everyone at the presentation was stunned to find out how much money was left on the table by not basing their activities on transactions, which could be cleanly tied to the participating citizenry and a variety of channel partners. There was over $38 million in annual benefits left over, which included partially recovered lost revenue, cost avoidance and reduction. A higher data impact to this revenue driven business model could have prevented this.
Given the total revenue volume, this may seem small. However, after factoring in the little technology effort required to “collect and connect” data from existing transactions, it is actually extremely high.
The real challenge for this organization will be the required policy transformation to turn the organization from “data-starved” to “data-intensive”. This would eliminate strategic decisions around new products, locations and customers relying on surveys that face sampling errors, biases, etc. Additionally, surveys are often delayed, making them practically ineffective in this real-time world we live in today.
Despite no applicable legal restrictions, the leadership’s main concern was that gathering more data would erode the public’s trust and positive image of the organization.
To be clear; by “more” data being collected by this type of government agency I mean literally 10% of what any commercial retail entity has gathered on all of us for decades. This is not the next NSA revelation as any conspiracy theorist may fear.
While I respect their culturally driven self-censorship despite no legal barricades, it raises their stakeholders’ (the state’s citizenry) concern over its performance. To be clear, there would be no additional revenue for the state’s programs without more citizen data. You may believe that they already know everything about you, including your income, property value, tax information, etc. However, inter-departmental sharing of criminally-non-relevant information is legally constrained.
Another interesting finding from this evaluation was that they had no sense of conversion rate from email and social media campaigns. Impressions from click-throughs as well as hard/soft bounces were more important than tracking who actually generated revenue.
This is a very market-driven organization compared to other agencies. It actually does try to measure itself like a commercial enterprise and attempts to change in order to generate additional revenue for state programs benefiting the citizenry. I can only imagine what non-revenue-generating agencies (local, state or federal) do in this respect. Is revenue-oriented thinking something the DoD, DoJ or Social Security should subscribe to?
Think tanks and political pundits are now looking at the trade-off between bringing democracy to every backyard on our globe and its long-term, budget ramifications. The DoD is looking to reduce the active component to its lowest in decades given the U.S. federal debt level.
A recent article in HBR explains that cost cutting has never sustained an organization’s growth over a longer period of time, but new revenue sources did. Is your company or government agency only looking at cost and personnel productivity?
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 and benchmarks. 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 warranty or representation of success, either express or implied, is made.
For years, a customer’s purchase process was something of “An Unexpected Journey.” Lack of insight into the journey was a struggle for retailers. The journey was fraught with questions about product research habits, purchases and crucial factors that spark purchase decisions.
Today, the customer purchase journey no longer has to be a “guessing game.” Data integration and analytics are able to assist retailers in understanding this journey. To begin, let’s examine how consumer behaviors and the role of product information have changed since the advent of substantial bandwidths and social buying. To do so, lets examine the way shoppers buy today.
The customer buying experience has changed in the following ways:
The days of the single visit to a trusted retailer are behind us. Today’s shoppers are in control. They are hugely aware of their power as consumers, and they’re exercising it freely.
Buyers aren’t using one specific channel anymore. They’re shopping in stores, online, through mobile apps, on social platforms, and from catalogs simultaneously. Lacking a central focal point, quality data integration and analytics have become imperative to understanding this behavior. Retailers must be able to track the purchase decisions of one consumer as he or she switches back and forth amongst these channels. If done correctly, a retailer would be able to recognize behavior specific to individuals and act on it, serving ads or timely discounts to them.
Purchasing decisions are “crowd-informed.” Recommendations and reviews from peers guide consumers and validate their choices every step of the way. As a result, it has become increasingly necessary for retailers to understand how they are being reviewed. But more specifically, it is important for the retailer to identify and target influential reviewers. If this is done effectively, the retailer may be able to personalize their experience and make that influential consumer feel special. This may seem like a complicated task with small returns, but imagine if they write a positive review that is ultimately read by thousands of people. This could lead to a fantastic return on investment for the retailer.
Shoppers used to be dependent on a few sources of information. Now with Internet search tools, consumers are able to hunt for answers themselves. As such, retailers must understand what type of information their consumers are searching for. With this information, retailers may be able to update the content on their websites, blogs, or social channels to provide information customers need. To visualize this purchase journey we’ve created the INFAgraphic below.
So how can I learn more?
Join us at Informatica World 2014 to learn rich information about retail technology and the “purchase journey.”
Experts will share ways of leveraging your data to boost sales and heighten customer experience. The conference also has a dedicated MDM Day on Monday May 12 with workshops and sessions showing how vendors, distributors, retailers and individuals interact in the “always-on,” connected world.
Reserve your spot by signing up here.
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.
In a previous blog post, I wrote about when business “history” is reported via Business Intelligence (BI) systems, it’s usually too late to make a real difference. In this post, I’m going to talk about how business history becomes much more useful when combined operationally and in real time.
E. P. Thompson, a historian pointed out that all history is the history of unintended consequences. His idea / theory was that history is not always recorded in documents, but instead is ultimately derived from examining cultural meanings as well as the structures of society through hermeneutics (interpretation of texts) semiotics and in many forms and signs of the times, and concludes that history is created by people’s subjectivity and therefore is ultimately represented as they REALLY live.
The same can be extrapolated for businesses. However, the BI systems of today only capture a miniscule piece of the larger pie of knowledge representation that may be gained from things like meetings, videos, sales calls, anecdotal win / loss reports, shadow IT projects, 10Ks and Qs, even company blog posts – the point is; how can you better capture the essence of meaning and perhaps importance out of the everyday non-database events taking place in your company and its activities – in other words, how it REALLY operates.
One of the keys to figuring out how businesses really operate is identifying and utilizing those undocumented RULES that are usually underlying every business. Select company employees, often veterans, know these rules intuitively. If you watch them, and every company has them, they just have a knack for getting projects pushed through the system, or making customers happy, or diagnosing a problem in a short time and with little fanfare. They just know how things work and what needs to be done.
These rules have been, and still are difficult to quantify and apply or “Data-ify” if you will. Certain companies (and hopefully Informatica) will end up being major players in the race to datify these non-traditional rules and events, in addition to helping companies make sense out of big data in a whole new way. But in daydreaming about it, it’s not hard to imagine business systems that will eventually be able to understand the optimization rules of a business, accounting for possible unintended scenarios or consequences, and then apply them in the time when they are most needed. Anyhow, that’s the goal of a new generation of Operational Intelligence systems.
In my final post on the subject, I’ll explain how it works and business problems it solves (in a nutshell). And if I’ve managed to pique your curiosity and you want to hear about Operational Intelligence sooner, tune in to to a webinar we’re having TODAY at 10 AM PST. Here’s the link.
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
The challenge for supermarkets today is balancing the needs of the customer against their ability to serve those needs. How are supermarkets and food manufacturers preparing their business for e-readiness? What about more customer centricity?
Currently, brands are not particularly good at serving consistent product information across in-store and online environments, leading to lower conversions and poor customer satisfaction. This shortfall is also preventing these brands from moving forward and innovating with new technologies. As a result, Product Information Management (PIM) is becoming a significant focus in effective omnichannel initiatives.
Consider the large range of products that can be seen at the average grocery store. The sheer number of categories is staggering, before you even consider the quantity of items in each category. There’s little wonder of local brands are struggling to replicate this level of product data anywhere else but on their store shelves.
Furthermore, consider the various kinds of information supermarkets are expected to include. Then, add to this the kinds of information supermarkets could include in order to present a competitive advantage over and above the rest. Information types currently possible are: Ingredients, additives, Images and videos, marketing copy, gene manipulation information, references, product seals, allergens, nutritional facts, translations, product categories, expiration/use-by dates, variants, region-specific information, GSDN information and more.
Ultimately, supermarkets are already on the path of improving consumers’ shopping experience and a few of the emerging technologies indicate the way this industry will continue to evolve.
6 Examples of food retail and supermarket trends
The below six examples demonstrate an emerging trend in grocery shopping, while also highlighting the need for accurate product information creation, curation and distribution.
- Ready-to-cook product bundles: Nice and very customer facing concept is done by German food retailer www.kochhaus.de (meaning house of cooking). The only offer product bundles of all ingredients which are required to cook a certain meal for the required number of guests. It can be seen as the look books which are well established at fashion brands and retailers sales strategy.
- Self-checkout Systems – More supermarkets are beginning to include self-checkouts. American and UK companies lead, Germany or Australia are behind. But there is the same risk of cart abandonment here as there is online, so providing a comprehensive and rich suite of product information at these POS systems is crucial.
- In-store Information Kiosks – Some supermarkets are beginning to include interactive displays in-store, with some even providing tablets mounted onto shopping trolleys. These displays serve in place of an in-store sales assistant, providing consumers with directions, promotions and complete access to product information (such as stock levels) on any item in the store.
- Supermarket Pop-ups – Food retailers are increasingly experimenting and improving the traditional shopping experience. One example that has turned the bricks-and-mortar concept on its head is electronic shopping ‘walls’, where products are prominently displayed in a high-traffic area. Consumers are able to access product details and make purchases by scanning a code presented alongside the image of a given product.
- Store-to-door Delivery Services – It’s starting to become commonplace. Not only are supermarkets offering same-day delivery services, the major brands are also experimenting with click and collect services. These supermarkets are moving toward websites that are just as busy and provide as much, if not more relevant content as their bricks-and-mortar outlets.
- App Commerce: Companies, like German food retailer Edeka offer an app for push marketing, or help matching customer profiles of dietary or allergy profiles with QR-code scanned products on the shopping list within the supermarket app.
What is next?
The supermarket of the future:
Reviving Customer Loyalty with leveraging information potential
Due to the increased transparency brought on by the ‘Google Era’, retailers have experienced a marked decline in customer loyalty. This concept of omnichannel shopping behaviour has led previously loyal customers to shop elsewhere.
Putting customers in the centre of all retail activities may not be a new trend, but in order to achieve it, retailers must foster more intelligent touch points. The supermarkets of the future will combine both product and customer data in such a way that every touch point presents a uniquely personalised experience for the customer, and a single, 360-degree view of the customer to the retailer.
The major supermarket brands already have comprehensive customer loyalty programs and they’re building on these with added products, such as consumer insurance packages. However, these initiatives haven’t necessarily led to an increase in loyalty.
Instead, the imperative to create a personal, intimate connection with consumers will eventually lead to a return in loyalty. The supermarket of the future will be able to send recipe and shopping list recommendations directly to the shopper’s preferred device, taking into account any allergies or delivery preferences.
Gamification as a tool for loyalty?
Moreover, this evolution will slowly lead into another phase of loyalty marketing: gamification. Comprehensive and detailed product data will form the basis of a loyalty program that includes targets, goals and rewards for loyal customers. The more comprehensive and engaging these shopping ‘games’ become, the more successful they will be from a marketing and loyalty perspective. However, the demands for detailed, accurate product information will also increase accordingly.
Private side note: My wife likes the simple Edaka App Game, where users need to cut slices of sausages. The challenge you need to hit exactly the weight the customer requires, like the in-store associate.
Those supermarkets that can deploy these initiatives first – and continue to innovate beyond this point – will have a bright future. Those that lag behind when it comes to leveraging their information and real time process might quickly begin to fade away.
What can I cook of my fridge remains?
I have been working all week long on the next year planning, so my fridge was not feeded well this week. Being almost empty the asks are
- What products are left?
- When do they expire?
- What can I cook of my fridge leftovers? (receipts)
- Where do I get the missing items for dinner with my wife? – And for which price
- Do they all match with my dietary and here allergy to nuts?
- Can I order online?
- When will they get delivered?
- What things can make our evening a success? The right wine recommendation? Two candles?
Well it is up to your imagination which products also can be sold in addition to make the customer happy and create a nice candle light dinner… But at least a good reason to increase the assortment.
Unlike some of my friends, History was a subject in high school and college that I truly enjoyed. I particularly appreciated biographies of favorite historical figures because it painted a human face and gave meaning and color to the past. I also vowed at that time to navigate my life and future under the principle attributed to Harvard professor Jorge Agustín Nicolás Ruiz de Santayana y Borrás that goes, “Those who cannot remember the past are condemned to repeat it.”
So that’s a little ditty regarding my history regarding history.
Forwarding now to the present in which I have carved out my career in technology, and in particular, enterprise software, I’m afforded a great platform where I talk to lots of IT and business leaders. When I do, I usually ask them, “How are you implementing advanced projects that help the business become more agile or effective or opportunistically proactive?” They usually answer something along the lines of “this is the age and renaissance of data science and analytics” and then end up talking exclusively about their meat and potatoes business intelligence software projects and how 300 reports now run their business.
Then when I probe and hear their answer more in depth, I am once again reminded of THE history quote and think to myself there’s an amusing irony at play here. When I think about the Business Intelligence systems of today, most are designed to “remember” and report on the historical past through large data warehouses of a gazillion transactions, along with basic, but numerous shipping and billing histories and maybe assorted support records.
But when it comes right down to it, business intelligence “history” is still just that. Nothing is really learned and applied right when and where it counted – AND when it would have made all the difference had the company been able to react in time.
So, in essence, by using standalone BI systems as they are designed today, companies are indeed condemned to repeat what they have already learned because they are too late – so the same mistakes will be repeated again and again.
This means the challenge for BI is to reduce latency, measure the pertinent data / sensors / events, and get scalable – extremely scalable and flexible enough to handle the volume and variety of the forthcoming data onslaught.
There’s a part 2 to this story so keep an eye out for my next blog post History Repeats Itself (Part 2)
Everyone knows that Informatica is the Data Integration company that helps organizations connect their disparate software into a cohesive and synchronous enterprise information system. The value to business is enormous and well documented in the form of use cases, ROI studies and loyalty / renewal rates that are industry-leading.
Event Processing, on the other hand is a technology that has been around only for a few years now and has yet to reach Main Street in Systems City, IT. But if you look at how event processing is being used, it’s amazing that more people haven’t heard about it. The idea at its core (pun intended) is very simple – monitor your data / events – those things that happen on a daily, hourly, minute-ly basis and then look for important patterns that are positive or negative indicators, and then set up your systems to automatically take action when those patterns come up – like notify a sales rep when a pattern indicates a customer is ready to buy, or stop that transaction, your company is about to be defrauded.
Since this is an Informatica blog, then you probably have a decent set of “muscles” in place already and so why, you ask, would you need 6 pack abs? Because 6 packs abs are a good indication of a strong musculature core and are the basis of a stable and highly athletic body. It’s the same parallel for companies because in today’s competitive business environment, you need strength, stability, and agility to compete. And since IT systems increasingly ARE the business, if your company isn’t performing as strong, lean, and mean as possible, then you can be sure your competitors will be looking to implement every advantage they can.
You may also be thinking why would you need something like Event Processing when you already have good Business Intelligence systems in place? The reality is that it’s not easy to monitor and measure useful but sometimes hidden data /event / sensor / social media sources and also to discern which patterns have meaning and which patterns may be discovered as false negatives. But the real difference is that BI usually reports to you after the fact when the value of acting on the situation has diminished significantly.
So while muscles are important to be able to stand up and run, and good quality, strong muscles are necessary to do heavy lifting, it’s those 6 pack abs on top of it all that give you the mean lean fighting machine to identify significant threats and opportunities amongst your data, and in essence, to better compete and win.
How often are you getting emails with “your personal product recommendations”? How personalized and correct are they really? How relevant is your omnichannel information to your customers? Commerce Relevancy is the next wave putting Omnichannel Commerce on another level.
As Information gets more democratic, connecting the dots between master data of customers, supplier, location and products ring the bells for the next commerce wave after omnichannel commerce: It is Commerce Relevancy: In the first phase it is focusing and combining product and customer data to deliver consistency and relevancy in omnichannel retailing. That will have deep inpact in customer experience.
The evolution of the retail environment, driven by advances in technology, has taken us from single channel or siloed channels to omnichannel retailing. Customers expect to find product information and make purchases when it is most convenient to them. As a result, delivering the right product and brand information at every customer touch point has never been more important.
Consistent and accurate product information has a profound impact on the buying decision, but in this hyper-connected world where competitive information is at the customer’s fingertips, retailers and CPG manufacturers also need to ensure that the information provided is highly relevant in order to differentiate and stay ahead.
The market has passed the eras of siloed channels to multichannel commerce (serving all channels, but not allways connected, then connecting the channels, called cross channel commerce. The last wave was establishing the term of omnichannel commerce, due to Wikipedia described as “very similar to the evolution of, (Multi-channel retailing), but is concentrated more on a seamless approach to the consumer experience through all available shopping channels, i.e. mobile internet devices, computers, bricks-and-mortar, television, radio, direct mail, catalog and so on.”
The new generation of Commerce Relevancy requires the right information and data which help turning data into a competitive advantage by helping organizations present product information that is complete, accurate and easy to understand. In today’s retail environment data consistency is key, but it is no longer enough. Every retailer wants to be a success full online retailer and every manufacturer wants to become a retailer with several own direct sales channels.
The next wave taking omnichannel commerce to the next level will address information relevancy at every channel and all customer interactions – called Commerce Relevancy.
In order to enable Commerce Relevancy, companies are now asking themsleves how to connect the dots between supplier, location, customer and product information. In this business use cases customer profiles or target group personas get match with product inforomation in sales and marketing. Think of the same TV flatscreen sold to two completely different personas, but using other parts of the description to tailor it to the customer. Using other channels to promote it. Using other images and vidoes which match with the customer profile. Commerce Relevancy means connecting the dots between all master data and product information.
4 Elements of Commerce Relevancy
Relevance commerce is taking omnichannel commerce to the next level now. Commerce Relevancy is influenced by four main characters:
- Relevant product recommendations everywhere: what is the next logical buy? This will not only be leveraged in ecommerce but at any customer touch point.
- Relevant locations: the ways of a product from an own warehouse, from a supplier warehouse and brick and mortar become more flexible. Customers are being served always from the location nearby.
- Relevant marketing: personalization will reach a new level combining product, location, supplier and first of all customer information the right way and across all channels. Relations of and between data (like customer profiles and product bundles) build the core of customer experience, when delivered in real-time.
- Relevant analytics: As customers expect real time information and services new technologies come up to use eye mark recording or image recognition of customer faces when customers returning into a store. Measuring the heart frequency to understand customers’ emotions while shopping opens new possibilities, when connecting the data to unleash information potential.
Do you know how good your multichannel data is? This blog covers four business objectives when accelerating multi channel commerce and which quality of product data is needed to deliver to that and a summary of questions to ask when establishing your strategy. These questions help ecommerce managers, category managers and marketers at retailers, distributors and brand manufacturers ask the right questions on product and customer data when establishing a multi channel strategy.
The Multichannel Challenge: Availability of Relevant Information
At every customer touch point, the ready availability of product information has a profound effect on buying decisions. If your customers can’t find what they’re shopping for, don’t understand how well your product meets their needs, or aren’t confident in their choice, they won’t complete their purchase.
When customers are researching or actively online shopping for products, research says 40 is the magic number:
40 % of buyers intend to return their purchase at the time they order it.
40 % order multiple versions of a product.
40 % of all fashion product returns are the result of poor product information (Consumer electronics are 15,3%; Sources: Trusted Shops, 2012, Internet World Business 7.1.2013)
All the high-quality product data in the world is useless if an organization cannot leverage that data for quicker time to market, improved e-commerce performance, and greater customer satisfaction.
Four Business Objectives When Accelerating Multi Channel Commerce
This white paper comes with four common use cases that illustrate typical business objectives within a multichannel commerce strategy. When looking into your product information, here is a list of questions you might consider.
1. Increasing conversions and lowering return rates by ensuring that customers can access product information in an easy-to-consume form.
- Where is the flawed content coming from?
- What tools and incentives can we provide for suppliers to maintain the high quality content?
- Which data quality processes should be automated first?
- Do we need a bespoke data model to fit your requirements?
- Can we effectively use industry standards for communicating with suppliers (such as GS1 or eClass)?
2. Lowering manual processing costs by merging the best product content from multiple suppliers.
- How many product catalogs do we have and what are the processes that slow us down?
- Who is responsible for the quality of the product information?
- How can we define and enforce the objective and measurable policies?
- Which supplier has best descriptions / certain translation, high-quality images / video / etc.?
- How do we collaborate with our large and small suppliers to achieve best data quality?
3. Growing margins through “long tail” merchandising of a broader assortment of products.
- Can we automate product classification?
- Which taxonomy will work best for us?
- Do all stakeholders have visibility of data quality metrics and trends?
- How can we leverage information across all channels and customer touch points, not only ecommerce?
4. Increasing customer satisfaction through more consistent information and corporate identity across sales channels.
- How should we connect customer and product information to provide personalized marketing?
- How can we leverage supplier and location data for regional marketing?
- How do we enable crowd sourcing of comments, reviews and user images?
- What information do internal and external users need to access in real time?
Find more information with the complete white paper on multichannel commerce and data quality.