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#BigData #Customersegmentation #Customerservice #Geo-targeting #Location-based #Marketingindustry #Productcrossselling #realtime #dataanalysis

Home / Blog / Tag: #BigData #Customersegmentation #Customerservice #Geo-targeting #Location-based #Marketingindustry #Productcrossselling #realtime #dataanalysis

Data-driven business competitive advantages

Data is now one of the most important corporate resources. It’s helping more and more companies to anticipate future actions through their past activity. Regardless of whether they want to optimize their business processes with data-driven approaches, or expand or improve the interaction with customers based on data, or even introduce a new digital business model. They can diversify their portfolio with a range of different products – from classic to computerized to data-driven – in order to meet increasingly complex customer needs.

Data-driven business competitive advantages

In this context, Data-driven business models are increasingly becoming a decisive factor in competition. More and more companies are asking themselves how they can use data profitably in their business. But one should know that success does not depend on the pure availability of infinite (often unused) amounts of data. The challenge here is to combine structured, partially structured and unstructured data from different contact points with customers such as social media, sensors, mobile devices, sentiment data and call logs. With the right analysis of the data, more targeted marketing campaigns and better customer integrations desired results are achieved.

 

The analysis of data offers many advantages. Here below is a selection of possible application scenarios:

 

  • Analysis of customer behaviour: Insights and actionable information are gained through data analysis such as how the customers interact with your company so you can uncover ways that can better suit your customers’ behaviour patterns and increase your conversion rate.
  • Profiling of customer groups: Trends and patterns can be identified such as which customers looked at which products for how long? This also gives the opportunity to tailor the future collection to the tastes of certain customer groups. The importance of this process cannot be overestimated, especially for small businesses with limited resources.
  • Dynamic pricing: Thanks to analytics, companies can adjust their prices in real-time according to the market demand, consumer behaviour, available inventories and competitive situation as well as to financial targets and delivery conditions.
  • Personalized customer journey: Today’s customers are interacting with companies across multiple channels. Therefore, touchpoints across all those channels must be analysed so that a personalized and precise approach with the individual offers can be offered. AKA, The right product at the right time at the right price.
  • Next Best Action: Automated suggestions for further campaigns, special prices, additional offers, the type of customer approach (e.g. e-mail or telephone) or the intelligent control of online campaigns enable companies to track a dynamic view of their customers and use this information to better anticipate customer needs.

 

The data thinking concept is definitely a key to corporate success, which is based on data. Data-driven businesses open up countless possibilities such as improved customer and market knowledge, better coverage of customer needs, better sales forecasts, more targeted marketing, higher efficiency and much more. The first step is to look inward and work with the data that is already available to develop and advance use cases. The focus must be put on customer needs and the sensible implementation of the use cases so economic success and a positive ROI can be guaranteed.

Data Migration: How to overcome challenges during the migration process?

Every IT organization regularly faces the challenge of having to migrate data. Whether from the old memory to a new one, or straight to the cloud. A data migration is more than copying from A to B, especially due to increasing amounts of data and systems that are becoming more complex. Companies must ensure that data migration to a new storage system works smoothly before getting into the entire migration process.

As data continues to grow in importance, data migrations become top priority projects. A failure of migrations can lead the organization into a disastrous situation. For a successful migration, there are many factors to consider. Das these process are complex and require a high level of expert knowledge is required to ensure they go smoothly. Organizations that identify potential problem areas before the migration and plan accordingly ahead of time save time and money on their migration projects. Here below is a list of few but most common data migration problems.

 

Poor data management: Without a holistic overview of your data, it will be challenging to migrate it in a planned, correct and fast manner.In the absence of regular data management, the data lays in an unstructured manner across different systems – and leads to loss of production because important information is either  hard to access or no longer available. Poorly managed data is also expensive because those responsible are constantly expanding memory in an uncoordinated manner. As the migration of grown databases can consume a lot of time and money, it is highly recommended to clean up the data structure in advance to get rid of legacy issues and to optimize storage costs.

 

Manuel migration: Manually migrating an organization’s huge sets of data takes a lot of time and energy & resources. In particular, when data accumulated over decades have to be processed, manual migration is impossible and error-prone. As a solution, company can anticipate automating repetitive parts of migration with advanced migration tools. Not only process automation saves time and money but also increases the quality and data security.

 

Changing the storage system:  The problems with storage migrations increase when an IT administration wants or has to migrate not just to a new array, but to a completely new system – for example when changing providers or when a contract ends. The new system must then be set up in such a way that it behaves exactly like the old one. Otherwise due to the incomplete integrated into the overall IT infrastructure and cause issues.The team responsible for the migration must configure the target systems thoroughly and carefully before the migration.

 

Recognise and avoid copy errors through the verification process::  Project leader responsible for migrating data wants to be sure that it will arrive correctly at its destination. Incorrect coding of directories that are not displayed correctly can cause incorrect copying of the data in the storage systems involved. The log files of the migration, which many responsible persons use for the verification, cannot sufficiently confirm the correct migration, since they ignore possible weaknesses of the copy tools.

Instead, a modern verification tool can scan data, files and folders including metadata at the source and destination and compare them without further downtime. In this way, errors can be found and addressed. The verification of the data after migration using an independent tool with its own algorithm is essential. It is even mandatory in many sectors. The verification tool also documents the data status at the source and destination at the time of the switch, including the rights, so that the complete migration can be proven afterwards.

 

 

Migration are complex projects and require professional analysis, planning and implementation. The companies that have already set up professional data management have an advantage. If you have not yet implemented data management, or if you lack manpower, tools, know-how and expertise, it can be worth seeking advice from experienced data and migration experts or hiring them for both planning and in implementation. Feel free to talk to our experts about your existing or upcoming projects, we’ll be happy to help!.

Smart analytics: How sales and marketing can drive growth?

 

Digital technologies, particularly Social, Cloud, Mobile, and Big Data, are transforming the industry and the way companies used to operate. These technologies are creating new business opportunities by launching new services and/or establishing new businesses by optimizing operations, reducing costs, improving services, and/or launching new services along with companies.

 

Smart analytics, the most hyped term of the past couple of years, is still a catchall term. The ever-increasing amount of data generates enormous challenges, but also generates significant business opportunities for sales and marketing professionals of all sizes of enterprises. You must have noticed that in today’s ever-changing world, unstructured data such as digital photos, videos, and other connected social media activities are growing much faster than structured data so we can say that data processing is no longer the sole domain of relational databases.

 

Therefore, an entirely new industry has formed around technologies in order to store, sort, organize, and analyze the large volume of data and give business insights. Companies such as Xorlogics helps business to provide them with high-quality software, manage and transform their data, thanks to their deep expertise and leading-edge technologies that they have established in the areas of technology and development.

 

Ok so enough with the history and technology lessons, let’s talk about what does #BigData & #smartanalytics has to offer and how they can change the field of sales and marketing. Well, in my humble opinion, in terms of needs addressed and core functionality, Big Data can be seen as an evolution of business analytics and can be used in customer relationships better than ever before. A survey by Skytree ran in January confirms that sales and marketing gained the most from Machine Learning and advanced analytics projects. Basically now instead of giving ads in magazines and newspapers, or billboards and reaching out to only a limited local audience, it is time to start thinking outside of the box. Big data and predictive analytics technologies represent the opportunity to turn the tables. In other words, sales and marketing can finally become more about facts, analytics, and math rather than only a magical feeling of rather it’ll work or not.

 

Here’s how I think Sales and Marketing are gaining profits and new business opportunities by the correct input of Big Data and Analytics.

 

Customer segmentation:    

By using correctly the analytic tools, one can segment the market into granular micro-segments and then offer personalized services and increase effectiveness, efficiency, and satisfaction. Data analytical tools let you personalize marketing and campaigns, promotions and discounts, and customized goods and services. One can even get the prediction and advanced analytics of customers buying behavior at a nearly “personal” level

 

Social & mobile media real-time data analysis:     

Gathering and tracking real-time data from the Web allows adapting and evaluating business strategies and marketing champagnes that respond best to web-based consumers’ behavior and choices. Real-time sales data visualization technologies enable sales managers to adjust battlefields tactics based on live data feeds.

 

Product cross-selling:            

The best opportunity of cross-selling by using all the data that can be known about a customer, including the customer’s demographics, purchase history, preferences, real-time locations, and other facts to increase the average basket size.

 

Dynamic pricing:        

Increasing the level of granularity of data on pricing and sales – Pricing optimization leveraging demand-elasticity models based on analysis of historical sales to derive insights – Assessing and informing pricing decisions in near real-time. – Integrating promotions and pricing seamlessly, whether consumers are online, in-store, or browsing a catalog – Leveraging performance-based pricing plans and risk sharing schemes.

 

Location-based marketing and sales:          

The growing adoption of smartphones and other personal location data-enabled mobile devices to target consumers who are close to stores or already in them and let customers “check-in” in their favorite places. By geo-targeting mobile advertising, companies can create a multichannel experience to drive sales, customer satisfaction, and loyalty and create value from the use of personal location data.

 

Customer service:      

By developing product sensor data analysis for after-sales service, big data can be used to predict purchases, analyze customer behavior and better understand the people buying your product.

 

In conclusion, I’ll say that it’s true that large enterprises were the first ones to adopt BigData because their need to explore and gain insight from their enormous data is profound in comparison to a small business, however, if you delay a lot, you will be left alone far behind in this high-tech connected world. So more quickly you adapt changes to the tsunami of data and powerful business insights, the better impact your business can get!

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