Decisions @Speed of Business


These are times that companies need to show serious improvement in their decision making processes in turning data into decisions and actions. Even though in a world we talk about artificial intelligence and robots we have gone too fast creating automated decisions in digitalized processes, we still couldn’t catch this flow at companies with organizational hierarchies.

Most of the business decisions are made by humans as they are unstable and should be flexible according to the current situations in operational processes. When making these sort of data related to business decisions it is important to process the operational data as if it is done for raw petrol. At this point, as it is impossible to start a car engine with raw petrol, it is not possible to create meaningful actions for companies who don’t provide data insights for their decision makers.

The increase in data volume is higher than the data that turned into meaningful insights.  Within the past year, the companies which have data volume over 100 terabytes had doubled it. We are drowning in the data! However, the companies use only %20 structured data and only %10  unstructured data(social media, contacts, calls, video, sensors,etc.) in their decisions(*). Unfortunately, the % of used data will decrease, if we add filters to these decisions like smart, automated and optimum. The companies stuck themselves to a narrow window when using the data! “Drowning in the data, but not starving for insights” problem is caused by 3 main reasons: human, processes, and technology. The human-related reason is mainly caused by lack of teamwork between Business and IT teams when taking actions to increase data-driven business management process.  What has to be done in technology for data management is always the same for years. But due to working dynamics, it is impossible to realize it. As it is always the top priority for new store openings, campaigns, etc. for Business teams. When it is not a priority for Business teams to define an approach to their business management types, It is hard to expect big achievements with IT team’s solutions.

The most critical problem is the lack of the data-driven management approach from top to end decision makers in taking a business decision by looking into the right indicators for each process. When this approach is not adopted, the limited employees or data scientists will not contribute to the company. Even with the simplest BI tools, the results will be either subjective or unrelated to the real business processes.

%66 (*) of the companies keep their reporting and analysis data in excel. In other words, they don’t have a data-driven management approach! Decisions are taken either according to the personal expertise or thoughts on data sets gathered from manual BI tools and/or excel sheets. %34 of the companies get results of their decisions at the speed of business (**). For example, getting data to find an answer on why “A” product sells more than “B” or the profit decrease in “C” category will take with their entire tools and infrastructure. Only %3 of companies can create critical insights.

In order to increase data-driven management approach, it is a necessity to built a system to create calculated indicators and insights for decision makers other than letting them drowning in big data. Otherwise,  instead of having as many insights as we can get from our data, we will end up spending more time on analyzing data, calculations and getting insights, getting false results due to personal insights.

Sources: (*)Business Technographics Global Data and Analytics Survey, Forrester, June 2017.

(**) Augmented Analytics Is the Future of Data and Analytics, Gartner, July 2017.

2 Basic Requirements Of A Retailer Aiming To Reduce Inventory


The retail industry is undergoing a big change in terms of inventory. As you know, in many countries, inflation figures were very high in the 90’s, inevitably affecting the retail business. The most critical limitation in this space was – ironically – the limited space available. The economic landscape changed in the 2000’s.  These were the years when the executives figured out that piling up is not contributing to the bottom-line, on the contrary, it is a pretty bad idea. The concept of ‘Minimum stock level’ emerged and changed the inventory management approach. After almost 2 decades, supply chain professionals are still chasing the answer to a  question, where the bar is continually rising; “How can I make my minimum stock policy, even smarter?”. We will discuss in this and our upcoming posts, what a retailer needs to answer this question with confidence.

The 2 main prerequisites of a minimum inventory management approach  are;

1.Demand Forecasting System

It is no secret that, the success of an inventory management strategy is highly dependent on estimating the demand with the smallest error margin possible. While data flows from origin to the end, each step of the supply chain interacts with one another. Forecasting the demand is the first step of any production system and contributes to maintaining the stock levels, providing better service to customers, improving capacity utilization and bottom-line. Other than these, workforce, materials and capacity plannings are made based on forecasts. It is almost impossible to plan and manage in the absence of a solid forecast.

Retail demand is highly affected by discounts, campaigns and special day events, along with the seasonality and trend effects. To add another challenge, in retail it is common to see items removed from sale and then put back again, for certain business-related decisions. This fact distorts the time series and diminishes the confidence in the forecasts.

With a glance to retail, we see that some stores are located in city centers, some on university campuses, near stadiums, in the airports or on the coastline –  heavily affected by seasonal influences. A store in or near the university campus is directly affected by the academic calendar, as a store near the stadium is influenced by the league table. If the products determined to be affected by the special events or dates are not available in the stock room of the stores, customer demand will not be transformed into revenue. Since the effects are of different origins and nature, using a single method to compute the forecasts is not very realistic, after all. For this reason, we employ a multi-algorithm approach. We develop demand forecasting algorithms and race them to select the champion. We choose the best among the forecasting methods (exponential smoothing, regression, Holt-Winters, etc.) according to the nature of the demand and business.

2.Inventory Control System

The results derived from the demand forecasting system are input to the inventory control system. Thus every night, our system checks the constraints; customer service level, the rolling number to box quantity and stock on hand, decides whether the store needs to place an order on any specific product and if the answer is positive, computes the appropriate order quantity.

The value to carry less inventory grows each day and we believe that ignoring the data mining approach and maintaining the inventory management with human intervention hurts the business.

On our next post, we will detail the multi-algorithm structure in  demand forecasting.

Trends that will continue to rise in 2018 ( Part I)


“Change is the only constant thing” said Heraclitus – the philosopher from Ephesus who lived BC, 535-475. We already lived the first 2 months of the new year and we are curious about the advancements we will encounter in 2018 and as a player in the information technology space, I want to talk about what the industry should expect and how it will evolve.

In 2018 the trends of the previous year are expected to rise and converge. I will make my points in five headlines and this post will host the first two; Mobile and IoT.

Mobile: In 2018, mobile apps will continue to offer the customers a unique experience in the physical store and online, offering recognition, personalization, and interaction. In 2010, the share of mobile commerce in total digital commerce was around 2%, but today it is more than 20%. This increase will continue for sure, however, it is foreseen that around 2020, business models providing services on voice and AR will enhance the customer experience, make it easier & more natural and this may reduce the impact of mobile.

Considering that checking a mobile device frequently and looking at it for a considerable time brings some negative health issues, Voice and AR –  technologies that deliver experiences more suitable for the human nature –  will gain ground.

In 2018, mobile will play an effective role in sales conversion and payment. With more advanced barcode recognition standards and image recognition technology, products will be scanned easier and this will help increase the usage. Recently, Kroger announced that they will launch a new concept called ‘Scan, bag, go’ that will enable the customer to use their own device (or a device provided in the store) for checkout and payment, with no need for a cashier.  This was an extraordinary announcement since this was the first time that a checkout model with no cashier will be running in a considerable number of stores.

Store associates will use the mobile devices more effectively and efficiently while giving service to the customers. Especially for retail segments where customer service is crucial such as fashion or consumer electronics, the associate should have instant access to up-to-date information on the product and inventory, should be able to recommend other products, without leaving customer’s site. This will inevitably increase the impact of mobile in the store. Customer returns will be received with less effort by the staff using mobile devices.

 IoT: It is anticipated that in 2020, on a global scale, 34 billion connected devices will be on the market and $ 6T will be invested in IoT devices in the next 5 years. Which developments are supporting this rise? The decrease in sensor costs, the reduction in data processing costs, the reduction in bandwidth costs and the reduction in storage costs have great impacts on this growth. With these developments, the use of RFID will also increase. With this prevalence, retail customers will receive better service by accessing product reviews, high stock availability and digital coupons specifically used for the products with certain expiration dates, freshness and location. For in-house use, it will contribute to dynamic pricing and automatic ordering as well as real-time, up-to-date inventory and product information.

Combined with the blockchain, IoT exposed us to a new concept, BIoT.   BIoT – the combination of real-time and secure data – will emerge new business models. For example;  product traceability will be possible at last. Combined with the reliable environment provided by the blockchain technology, real-time data will make it easier to securely share business data across organizations, improving collaboration and efficiency, supporting collaborative business culture and customer experience.

I will continue the series in my next post and write on the impact of AI, blockchain and AR.

Highlights from NRF 2018


NRF 2018 took place between January 14th – 16th with the participation of retail industry stakeholders from all around the world, who want to keep the pulse of the future. I guess it would not be wrong to say the ‘Big Show’ turned out to be a ‘Tech Show’ as the focus in technology is increasing each year. I think the most important message of 2018 was that retailers who fall short to adopt technology – a real game changer – will have a hard time maintaining their position against the customer who is getting more digital and is changing the behaviors. The 2018 Technology Show was the exhibition on the effects of cognitive computing on customer experience. Although they have a broader portfolio of solutions, a significant number of information technology companies participated NRF with their cognitive computing, artificial intelligence and data-driven solutions, both in the exhibition and the conference sessions. There were 2 main missions that retailers and technology companies agreed on;

1. Customer expectations are augmenting day by day. We must further improve the Customer Experience.
2. We must use technology more effectively, not only for the customer but also to increase our business efficiency.

The prominent message of NRF 2018 for North America was the output of the Retail Economy Round Table. Gad Levanon, chief economist of the Conference Board North America division, predicted that consumer confidence would continue to rise and reach a record level. He stated that the 2017 holiday season had positive macroeconomic impacts on the 2017 economic figures. Retailers and vendors had consensus that 2018 will also have positive outcomes. Another critical issue was addressed in a panel chaired by David Marcotte from Kantar Consulting – Failures in international growth. The highlights were;

I. Problems in logistics and operations management, licensing and property management,
ii. Cultural adaptation; employee and product-related issues,
iii. Brand development; marketing, logo and naming can cause failure to grow in the international market,
iv. The payment methods, local parties in supply chain and logistics, compliance with law and taxation.

The most technology-focused scenario was based on a seamless customer experience with a highly efficient customer service; self-service and associate-free. Solutions like the components of an Amazon Go-style model retail in food retail were at the forefront. Fashion retail-focused solutions that detect customer’s body or foot measurements with 3D image sensors and recommend clothing or shoes based on this data, digital mirror or monitor used to order complimentary items for the one tried in the fitting room and systems that deliver customer comments on the selected item were the ones attracting most of the attention. I can express my takeaways from the event in 3 technology-nested headlines;

Restructuring of shopping processes:

We are witnessing that shopping starts with non-traditional methods. With kiosks running on augmented reality & hologram technology, smart shelves displaying information & 3D moving images on products and easier access to rich and real-time data, information technology has become part of our daily life. At the NRF, there were booths exhibiting vending machines – for consumer electronics, cosmetics and make-up retailers – which automatically recognize the customer and deliver an easy and secure shopping experience. It is possible to provide a better service to the customer without incurring square meter based costs. For example, Apple’s business chat application coming with iOS 11.3 in 2018 Q2, will enable the user to interact with the businesses without making a search on iMessage to find the business support accounts. The consumer will write a text and the message will be conveyed to the intended recipient; sales, customer services etc of the targeted company. Amazon Go, which started to serve the employees almost a year ago, was still an attraction point.

Focus on the importance of physical stores and sales staff:

Physical stores play a critical role in building relationships with the customers. 9 of the top 10 e-commerce companies have at least one physical store. However, physical stores are not utilized enough to further strengthen customer relationships. According to statistics, almost half of the Gen Y and Gen Z visit the physical stores, more than they did the previous year. The physical store is becoming much more critical to develop the brand’s relationship with the consumer, beyond shopping. This shows that a differentiated, more personal service and a better demand forecast will be more crucial. At this point, I have to mention the growing importance of the sales associates. The technological advancements serve the customers and increase customer satisfaction while they can also serve the staff and increase employee satisfaction. The sales associate applications – for the gusto-driven consumption retailers – that help the staff access the customer’s profile & purchase history, enable transfers of items across stores are powerful tools. On the other side, equally powerful tools for the grocery retailing are in-store applications helping the associate with shelf layout, inventory management – notifying critical conditions and enabling interaction of the staff. Thus, it is crucial to employ smart systems, mobile technologies and infrastructures both for building self-service customer experiences and for making real-time data available to the associates.

The importance of external factors in consumer demand, weather:

As in recent years at the NRF, the data-driven forecast and optimization had the leading roles. But the highlight was the automation of these smart systems. Another noteworthy concept was the importance of predicting demand based on external factors such as weather, local events and special days. Due to seasonal irregularities of our time, the weather seems to gain importance as a demand forecasting factor which highly affects the supply chain costs and planning. For example, the vending machines that are getting more popular day by day, utilize data such as the weather conditions of their exact location on the street and events/shows in the vicinity. Managing a business a vending machine efficiently is almost equivalent to anticipating the exact demand.

4 Ways Artificial Intelligence Will Penetrate in Retail


The use of AI technologies in the new generation enterprise and customer solutions seems inevitable. According to a research conducted by Gartner in 2016, AI was not among the top 100 technology areas to be invested. However, in 2017,  organizations and IT Managers made room on their agenda and AI ranked as the 7th technology investment priority. According to another recent Gartner study, AI will be built in most of the products that will be marketed by 2020. One of the top 5 areas where 30% of companies will invest will be AI-based solutions. Artificial Intelligence will also be a secret sauce, retailers will use as a game-changer, to support growth, to give customers a differentiated experience and to make a significant contribution to competitive advantage*.

AI will penetrate the processes with 4 main approaches;

  1. Minimize customer’s effort in shopping. From Augmented Reality to the rise of ChatBot, many of the emerging user experiences have a common point, accessibility and serviceability; anywhere, anytime. Today, we have come to the point where we can order coffee with a mobile assistant or ask a Facebook Messenger bot when we need an umbrella. The experimental store concept, which Amazon has just launched is a good example of effortless buying, empowered by AI.
  2. AI injected into the workforce. AI reaches every corner of the store’s back office processes and in-house operations, enhancing its effectiveness. Artificial Intelligence seems to help employees work faster, add value and be more accurate rather than stealing their jobs. The trainings will be delivered by AI, continuously and interactively. AR will help to service the customers with the products not present in the store or those not even produced yet. For example, Nike recently developed a store concept in NYC, called “Nike By You Studio” that allows the customers to design their shoes – with the help of a designer associate- and having them on their feet just after 90 minutes**. With this customer experience process characterized as “Nike Maker Experience”, the system uses AR,  object tracking and projection systems to show the selected design on the shoe.
  3. To take advantage of the opportunities provided by the platform economy. Business models like Ebay, have been working for decades on platform economy. Today’s platforms, integrated systems and IoT transmits the consumer’s requests directly to the manufacturer in real-time. Smart home “hubs” are offered over platforms like Samsung, Google, Apple and Amazon. For example, by pressing a button (Amazon), a user can place an order for a laundry detergent or diapers. If you like the song you listen to on your smart speaker, you can ask Microsoft Cortana to buy it for you.
  4. Focus on customer needs and redesign to facilitate the shopping process. Customer-related processes can be made more efficient and effective with modern engineering and design. Design-oriented engineering, also called “DesignOps”, works on processes that cause difficulties in customer interaction; such as problems getting product support or trying to find what they are looking for. Speech interfaces (chatbots), process automation, and AR can provide ways to deliver a better customer experience.

While we are already making room for AI in our lives, we have to be careful not to make the cure worse than the disease. Unexpected discomforts may come up by the use of AI or robots, in customer interaction or collection of personal data. It is critical to timely detect such inconveniences and to take quick actions, not to jeopardize the customer happiness.

Every new ‘digitalization’ and ‘intelligent automation evolution’ step will influence our lives significantly.  For this reason, businesses should be careful to act within the ethical framework while innovating and make sure they perform cross-tests to predict the effects of the new processes.

(*) Why retailers need to prepare for an AI- first world, today – and how they can. Avanade’s Tech Vision Report, 2017

(**) Nike’s new tech creates custom sneakers in under 2 hours, Stephanie Pandolph, Business Insider, September 2017.


A New Approach to Customer Engagement


Competition has always been a challenge, getting tougher every day. No secret that a business outstrips the rivals, only when the customers are satisfied and engaged. As Peter Drucker put beautifully; “The purpose of a business is to create a customer.”

To claim customer engagement, there should be customers, coming back over and over again, to purchase the products or services. It is critical to know the customer and predict the behavior, to take any possible action. We have been told that CRM is the approach and Loyalty Program is the tool, but that was some decades ago.

I witness that this perception didn’t give any ground since I still hear retail professionals say  “loyalty card is the way to collect the data and to know the customer”.

Oddly enough, the transaction logs conceal, so much more than the customers declare themselves, on a predesigned form.

I believe the reason behind the retailers’ assumption is, being stuck – for years – between RFM Segmentation with no reasonable action, campaigns sent out with bulk messaging and failure to personalize.

As technology advances and the processing power is more affordable,  we – technology providers – can easily incorporate mathematical models in our software and deliver you high-performance solutions. It is not a myth anymore; You can know your customer, better than him or her. With “Data-driven Behavioral Segmentation”, it is possible to develop a new approach to enhance customer engagement.

I would like to take this occasion to update you on what we have been working on lately, regarding this new approach.

  1. With no doubt, the online and offline channels should be integrated. The transactions made in the physical store and the online purchases should be aggregated on a customer record. Although there is progress compared to the early days of multi-channel, the pain point I get to hear the most is that the retailers cannot trace the customer who is ‘identified with an email address while shopping online’ and is ‘recognized with the phone number in the store’. In pursuit of the omnichannel, the retailers are having a hard time deduplicating the channel customers. Applying the Detailer Deduplication model, we helped retailers overcome this hurdle.
  2. We depict the ideal customer and the behavior set, extract all the alike-unlike sets and customers from an ocean of data. Certainly, this is a tough job, however using the Big Data approach, we are able to analyze with high performance and accuracy.
  3. Without the hassle of inputting the variables regarding the sales dynamics, marketing strategies, we work on the T-Logs to deliver the correlations. We incorporate data mining methods to extract the rule sets. We shed light on the probability of selling Y to customers who bought X, the lift factor of X to the sale of product Z.
  4. Predefined segment structures that encapsulate the customers in “not so accurate” groups are no longer needed. The new approach is to segment the clientele solely on behavior; monetary scale, the composition of the basket/categories or the timing of the purchase – weekday, weekend, morning, between 14:00-15:00.

Let me wrap it up!

Don’t lose time with the data collected at the first encounter, declared by the customer, filled in the boxes of a form designed by the retailer, which is no longer up-to-date. Take time to evaluate the Big Data & Data Mining solutions and bother only to collect the email and phone number from the customers, for communication & easier deduplication purposes. Your data has millions of stories to tell.

If this is on your agenda, let’s have a chat!

Listen to your data, make intelligent decisions.

7 Retail Customer Expectations Cognitive Computing Will Resolve in the Future


In a previous post- Cognitive computing and Customer Experience in Retail – I defined Cognitive computing as ‘the simulation of human intelligence & the thinking process;  thinking, reasoning, learning &  taking-action executed by the computer systems. In other words, it is an approach to perform the five human senses through information systems.’ We have been witnessing the critical changes in data-driven decision making and analytics systems & approaches, in the past years while creating solutions and initiating projects.

Let’s have a quick tour and understand how did we end up here?

In very early days, we started developing solutions for our customers to find the answer to their question “What Happened?”. After understanding this, the obvious question was “Why did it happen?” and we created solutions enabling interactive analysis, to find the answers. Any decent professional who knew the answers by then, started asking “What may happen?”, encouraging us to deliver our predictive solutions. Who can stop anyone to ask “What action should I take?” when they learn what is likely to happen in the future? Today the question evolved to the final – for now –  form. “What is the next best action?” and we are adopting cognitive computing approach, to deliver the answer.

According to the Louis Columbus research published in Forbes in March 2017, 70% of retailers are expected to run cognitive computing systems by 2021. Minimizing out of stocks with real-time inventory tracking and operation monitoring, providing better and more personalized services to the customers, will be embraced as ways of creating value.

With the solutions we offer, the retail industry has come to the point of making the right decisions automatically, with the real-time, operational and customer experience data they have in hand. The efforts to deliver a more personalized and high-quality service to the consumer, with less time spent on the consumer’s side, did not only increase the operational efficiency but improved the customer experience, as well.

We are now at the point where the consumers will start judging the industry norms, with simple but impressive styles.

A study published by Synchrony Financial in March 2017 reveals predictions about the future customer expectations. According to these predictions, we will soon meet the DIY consumer.

  1. Customers have already begun to gather more information from content providers such as, search engines and social media before they even come to the store. Some are more informed on a specific product than the sales associates, as they enter the store. In the future, the consumer will get the information via sensors on the products, pay with fingerprints or smartphones, without accessing any POS or waiting in the queue. The associate will be in the store as the expert, to be consulted.
  2. Fitting rooms with interactive mirrors will be the medium to call a different size, to put an order or even to pay.
  3. No need to wait for the store to open. There will be 24/7 sales. Even if the store is closed, orders will be placed at the storefront, delivery will be done by robots.
  4. Physical stores will be preferred for experiencing the product, entertainment, learning and getting help. For example, a 3D face modeling application, that perceives the face shape of a person will suggest a personalized model of eye-glasses. After the selection of one of the choices, 3D printers will be printing the final product, while the customer is in the store,
  5. Entertaining, having a good time, listening to a mini-concert or having a cup of coffee while shopping, attending a course to make artisan chocolate or an original leather belt in the store, reserving a fitting room; These are likely to be witnessed in the close future of retail.
  6. Customers will start asking “Why am I going to the store? Stores should come to me!”. With voice-driven systems, customers will expect the product or service to wherever they are, at home, in the car, etc, just by calling their name.
  7. Most important of all, the customers will be more time-conscious. They will expect to have what they want, right away. Customers will not settle for any delivery or return pickup that exceeds an hour.

As the expectation of the customer’s experience grows, we will look for an answer to the new question “How can we meet this expectation in  a better way?” Apparently; brands adopting systems based on cognitive computing will be differentiated in every field and will be leading the competition ahead.

4 Effects of Blockchain on the Retail Industry


Thanks to Bitcoin,  we have been talking about transferring money and shopping in different points of the world with no  central authority, almost for 8 years by now. Behind Bitcoin, there is a digital currency that comes into life through a reliable, cryptographic protocol –  blockchain  technology.

With Blockchain, digital data is not stored in centralized systems, but is kept in the form of linked records on multiple distributed systems. In a structure that can be described as a ‘digital registry’ held on millions of computers, transactions are stored in an encrypted form. The way to  exploit such a system,  is not  to hack a central – or any – computer. This doesn’t work. Since the chains are distributed to millions of computers, it is hopeless to change any record on all of them and abuse the system. In addition to being reliable, Blockchain also eliminates the financial middlemen. With Blockchain, access is granted only to users that are allowed to see the entities. All operations related to the digital registry can be done with absolute reciprocal confirmation on this reliable network where the information source is clear and transparent. In classical digital systems,  the transaction is conserved by a central authority while the parties receive a copy, whereas the distributed system grants direct access to the parties. Goods, services, payments, asset purchases can be done faster and with lower transaction costs.

All of this shows that the  Blockchain technology and Bitcoin that entered our lives with the finance sector but will seriously affect other spaces as well, especially retail;

  1. Source of product / authenticity: The main effect of the blockchain will be to provide consumers with more reliable and accurate information about the products they buy and the information they are sensitive to, such as the source, purity and content.  Consumers prefer retail chains that they can trust, when they have problems detecting the authentic and the fake.A recent survey shows that 40% of consumers who are  aged under 49 believe that products sold with organic qualification do not reflect reality and this is just a marketing tactic. The data provided with the blockchain can provide information down to the seed level  or the animal’s DNA.
  2. More reliable digital transactions and operations: Nowadays, payment transactions between consumers and business partners are executed via third parties, incurring speed and commission costs. Blockchain-based payments and transactions need no third party. Faster and abuse-free transactions will increase the efficiency of collaborative work and costs will be reduced. In particular, invoice matching, goods receipt and quality control processes will be improving. Organizations can shift their EDI (electronic data interchange) processes – where orders, invoices and delivery processes are registered – to blockchain.
  3. Supply chain traceability: In complex supply chains, product tracing and stock control become challenging and managing it needs enormous effort. As we all know, in the supply chains where product traceability is difficult, the bullwhip effect leads to the overstock. In addition to monitoring products with Blockchain, supply chain can be dynamically monitored and the conditions agreed upon on the smart contracts can be audited, enabling the work and payment orders to be dynamically  generated. Unsafe food  production and inappropriate distribution may be prevented at the source. As a result, product reliability, instant service quality control will be ensured and exploitation will be avoided.
  4. Network loyalty programs: While many companies try to broaden their loyalty programs beyond one brand, the loyalty apps running on multi-brands and multi-organizations are very popular by now. Blockchain can contribute with the real-time tracking, allowing points to be processed faster, cheaper and more reliably both for the brands and the customers of these loyalty programs. Customers can receive hyper-personalized suggestions and even have the ability to customize them, e.g. enabling the customer to exchange points with other users, enhancing customer loyalty and avoiding customer churn.

Cognitive Computing and Customer Experience


I have been writing on cognitive computing for a while. However, the effect of cognitive computing on customer experience and phygitalisation, increased my apetite to focus for this post.

Cognitive computing can be defined as the simulation of human intelligence & the thinking process;  thinking, reasoning, learning &  taking-action  executed by the computer systems. In other words, it is an approach to perform the five human senses through information systems.

Data-driven artificial intelligence is well utilized on either cloud or local infrastructures. In everyday life, we run into the cognitive computing functionalities, more than ever,  as natural language processing, voice & toning analysis, visual recognition, weather & location detection, bots and conversational commerce.

A recent Forrester research shows that;

– 45% of the online customers choose not to buy if they can not find quick anwsers to their questions.
– 50% of the potential sales are lost if customers can not find what they are looking for or can not get specialized services.

– 29% of online customers prefer to use the live customer service while shopping.

In fact, these outputs reveal some of the reasons behind the consumer visiting the nearest store in this age of digitalization; a direct and candid interaction with the store associate and getting personalized recommendations, prices & offers.

This brings us to the debate on the importance of monitoring the customer expectations momentarily in both worlds; online and digitalized physical stores.

In the past days, it was sufficient for the leading retailers to collect and make sense of  the behavioral and demographic data to provide differentiated customer experience. Today, the retailers find themselves in a business where they have to instantly capture all the data about consumer’s questions and remarks, to interpret them from an emotional perspective and to take action accordingly.

Good news is that, there is a way to transform this pain into a business solution; enabling such a relation between the retailer and the consumer.

The volume of the retail data doubled in the past year and the years ahead are promising a steeper growth in shorther timeframes. This huge data mass will be processed by cognitive computing on cloud or local hybrid computer systems, to deliver solutions to – continously and sustainably –  test the pulse of the consumer.

5 Reasons You Should Use Detailer CEO Dashboard

Dilruba Çelikkol |  Detailer Product Manager

To fulfill the need of  prompt decision making of our time with accurate information, CEO and the CxOs need a platform where they can see the state of the enterprise. This platform should carry all the KPIs needed to run the company, with a periodical and comparative monitoring. No need to mention that it should be accessible anywhere, anytime with highest security possible. Our resolutions to the above statements for the retail industry shaped the blueprints of Detailer CEO Dashboard. Detailer is a business analytics platform, transforms the data into reliable information and information is transformed into predictions, providing foundation for both real-time tactical and long-term strategic decisions of the retail managers.

And here I want to share  the 5 reasons you should use Detailer CEO Dashboard?

  1. It is mobile. You can reach any information and monitor your company 24/7, from every internet accessing corner in the world.
  2. All the information you need on one board. You do not get lost, in and out of the reports, chasing the related charts and losing track of what you were looking for in the first place.
  3. Has a straightforward interface, talking the retail language, which makes Detailer CEO Dashboard easy to use, comprehend and take action.
  4. The platform has all the KPIs, nothing more, nothing less.  All the metrics to manage a retail company is boxed in Detailer. The data you need is available in both summarized and detailed forms. You can always drill to see the details in a chart.
  5. The colors are talking. You just have to listen to them. If your dashboard is green as a golf course, your company is doing great. Beware if it starts to look like a Christmas tree with other eye-catching colors on it.

You, as decision makers are seasoned professionals with  profound business skills. However you need to listen to the stories your data are telling you, with the single version of truth, to keep the whole company aligned. You can do these effortlessly, in a heartbeat.