Donal Dunne

Donal Dunne

Why Retailers Forfeit the 30% Omni-Channel Premium

Why Retailers Forfeit the 30% Omni-Channel Shopper Premium

The Omni-Channel Shopper Premium

Omni-channel retailing has attracted a lot of attention in recent years – but many retailers still don’t realize its full potential. After countless man-hours and endless expense, they develop a multi-channel strategy across a range of sales and marketing platforms that is – well – pretty good. But is “pretty good” good enough? When sales and marketing platforms include ecommerce, social media, and mobile apps alongside more traditional methods like brick & mortar store, catalogues and kiosks, why do businesses leave their channel to market incomplete?

Maybe the problem lies in the widespread confusion about omni- vs. multi-channel initiatives. An omni-channel system takes a connected approach to multiple channels, seamlessly integrating customer activities into a single conversation, even when the customer decides, for whatever reason, to switch channel. In omni-channel retailing, the customer can select and change channels in any way that suits them – and the retailer can respond instantly to deliver the experience that the customer needs. Each time the customer interacts with the brand, they generate data that the retailer can use to better anticipate and serve the customer during the next conversation.

So, if omni-channel initiatives are so powerful, why are retailers not taking the next step?

Current Concerns

In a multi-channel system, a retailer grows from a single channel to multiple channels with each channel essentially operating as a separate business unit. Each has its own pricing, promotions, inventories, and back office systems. The omni-channel system integrates all of these channels and their accumulated data into one cohesive view of the business and customer. But many retailers wrongly believe that their organizational structure and systems don’t lend themselves to the new environment.

Many feel that a fundamental redesign of the corporate retail organization – from a single P&L regardless of channel, to “rip and replace” of IT systems – would need to occur at the most basic levels. And many organizations are unsure if the extra time, money and risk to reorganize is worth the advantages promised by an omni-channel strategy. In short, many retailers have adopted a wait-and-see stance before they invest.

However, these retailers can take comfort and guidance from the conclusions of the IDC FutureScape: Worldwide Retail 2015 Predictions conference. Based on a survey of top retailers, the conference predicts that “In 2015, CIOs will invest in omni-channel integration technologies as a top priority to support growth in the omni-channel shopper sales premium of 30%.“

The Future is Now

When retailers invest in omni-channel integration, they essentially design an entirely new supply chain of unified capabilities that can simultaneously handle the demands of their “brick and mortar” stores, their ecommerce sites, and any other channel that they have in place. The retailers that have already done so are already seeing the benefits:

  • Corporations that have invested in omni-channel services are already witnessing an average of 30% increase in sales.
  • The IT departments of these corporations are spending far less time performing the redundant or duplicate tasks required by a multi-channel system.
  • Both structured and unstructured data are more successfully and easily integrated across the company than with a multichannel operation.
  • IT departments can retire older technologies that are no longer performing at their previous levels of efficiency.
  • Consumer impacts on individual channels can now be identified almost immediately and the channels adjusted accordingly.

While many businesses may be cautious about taking the next step, the shopping characteristics of today’s consumer are rapidly changing. Customers are moving into an omni-channel world, whether the retailer is ready or not. This means that the business might be forced to play catch-up to their customers, and perhaps sooner than they might like. Omni-channel initiatives simply reflect, improve and realize the value of this customer behavior. Omni-channel initiatives are about making the individual consumer the main focal point of the business model.

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Posted in Customer Acquisition & Retention, Customer Services, Customers, Data Integration, Retail | Tagged , , | Leave a comment

Can Big Data Live Up To Its Promise For Retailers?

Can Big Data Live Up To Its Promise For Retailers?

Can Big Data Live Up To Its Promise For Retailers?

Can Big Data Live Up To Its Promise For Retailers? [/caption]Was Sam Walton, founder of Walmart talking about Big Data and Analytic in the 90’s when he said, “People think we got big by putting big stores in small towns. Really, we got big by replacing inventory with information.”  Walmart clearly understood the value of the large volumes of data they had access to and turned it into competitive advantage.

As retailers move from looking in the rear view mirror (what happened) to the road ahead (what will happen) they have turned to Big Data and Analytics for answers. While, Big Data holds great promise for retailers, many are skeptical. Retailers are already drinking from the data fire hose, whether its transaction data, recording every product sold to every customer across all channels or research data, covering detailed consumer profiles or web log and social data. The questions retailers are asking; will the investment drive more revenues, increase customer loyalty and create a more rewarding customer experience? Will I gain a deeper insight into customer transactions and interactions across the organization? Can we use existing resources and infrastructure?

The answer is Yes, Big Data presents the opportunity to better analyse everything from customer shopping behaviors at each stage of purchase journey, to inventory planning to delivering relevant and personalized offers. By analyzing how shoppers found your products, how long they spend browsing product pages and which products they added to their basket provides greater insight into what decision process they went through before purchase and helps retailers quickly identify cross sell and up-sell opportunities in real-time. In addition, combining transaction data and what your customers are saying on social channels (ratings, likes, dislikes, what’s trending etc.) can feed into the decisions you make on placing the right product, in the right store at the right price and ultimately deliver very personalize and contextual offers to the customers.

Data Driven Decisions Getting value from Big Data

Turning Big Data into actionable insight is not just about dumping data in to a “Data Lake” and pointing an analytics tool at it and saying job done!  Retailers need to take a number of steps to profit from Big Data and Analytics.

  • Firstly, you need to gather data from all available sources in batch or real-time, from internal and external, and from an ever increasing number of devices (beacons, mobile devices). Once you have gathered the data, it needs to be connected, validated, cleansed and a governance process put in place before integrating with analytic tools and systems.
  • Secondly, put clean and trusted data in the hands of data scientists who can distill the relevant from irrelevant and formulate commercial insights that the business can action and profit from it.
  • Lastly, plan and organize for success. IT and business need to align behind the same agenda, regularly reviewing business priorities and adjusting as needed. Maximize existing scare IT resources by leveraging existing technologies, Cloud platforms and forming alliances with 3rd party vendors to fill skills gap. Secure quick wins for your Big Data initiatives; maybe start with integrating historical transaction data with real-time purchase data to make personalized offers at point of sale. Look outside your organization and to other industries like retail banking or telecommunications and learn from their successes and failures.

With the right approach, Big Data will deliver the return on investment for retailers.

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Posted in Big Data, Retail | Tagged | Leave a comment

Bad Data Is Criminal

Reading a recent central statistical office report showing that burglaries, theft and fraud have increased in the last quarter reminded me of a how Humberside police use data and the information they extract from it to help fight crime.

It is easy to underestimate how tenacious the modern criminal can be in avoiding attention and capture by authorities, they are not motivated to provide accurate information when questioned! Moreover, any inconsistency amongst police departments or personnel in the way in which the data was entered could add to data quality problems, inadvertently aiding the criminal. (more…)

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Data Quality Helps Find Missing Revenue

The establishment and maintenance of accurate customer data is the key to all revenue-generating events that a company has. A single key question is at the heart of this: Do you understand your customers? And good quality data is at the heart of the answer to the question.

As an extension every organization must know who its customers are, what do they want? What did they buy?  This question appears straightforward, but it’s not uncommon for every department within a company – finance, sales, marketing, or customer service – to have a different answer because each has their own version of the customer data. (more…)

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Posted in Customer Acquisition & Retention, Customers, Data Governance, Data Quality, Telecommunications | Tagged , , , , | Leave a comment

Beauty Is Only Skin Deep

“Beauty is only skin deep”. This old saying came to mind recently when speaking with a friend. Jane was relaying to me the amount of time she spends correcting data for management reports every month. Answering simple questions like “how many new customers did we add?”, “how many customers placed repeat orders?” or “what was the top selling product?” Without the correct answers, management ran the risk of making poor decisions on future investments in marketing campaign, capacity planning and sales and support resources.

On average Jane spent two days a month checking for duplicate customer names and standardising product codes and descriptions, just so the reports would give an accurate reflection of sales. All this was managed in multiple Excel worksheets. The reporting tool the company had invested in was still being supplemented with manual worksheets, as management did not trust the information from the tool of choice. As the months and quarters went by Jane spent more and more time managing the worksheets. (more…)

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Posted in Data Integration, Data Quality, Profiling | Tagged , , , , , | 2 Comments