How to make your MVP the talk of the town

strategySo you are launching your product or planning a launch but are you sure your product is going to make the waves? You don’t want to be spending your time, energy, $$ and efforts on a product, in vain. Maybe you are still working in a 9-5 job and are testing the waters in the startup community? Then it becomes, even more relevant to get your ideas validated by a targeted audience before you take the plunge, lock, stock and barrel!

Let’s get discussing how you can be sure that your MVP is sustainable and creates the necessary ripples in the market.

  • Get feedback early in the process. Feedback from friends and family, who can be brutally honest with you. Doing so will also make you think deeply and clearly about your value proposition. Use your family and circle of friends to spread the word about your product.

          “If you can’t explain it simply, you don’t understand it well enough” – Albert Einstein

  • Meetup.com – Gather a bunch of like minded people and brain storm your ideas. You will find out if someone has already treaded the path you are planning, learnings and consequences. You just might stumble upon your business partner or a seed investor.
  • Social Media Marketing – Get going on the social media bandwagon, post information and images relevant to your product and get some feedback. Target your tribe through social media, utilise influencer marketing to check how your MVP is percieved. Follow other similar product brands and do some competitive analysis.
  • Explainer video – Shoot an excellent graphical and easy to understand video while at the same time highlighting the features that define your MVP. Get this video out there on social media and analyze the popularity.
  • Crowdsource – your branding and advertising efforts. Make your targeted customers be a part of the product development journey. They will not only feel connected to your would be product but also contribute to the making by with useful feedback. If they like it they’ll love to be brand ambassadors.
  • Demand Vs Supply – Last but not the least check the demand of the product you are launching. If there already exist a dozen such products then it probably will be an upphill task fighting the competition. Thinking out of the box and finding an area where there is a demand supply gap is the wisest thing to do unlesss your product is so radical that it changes the way people have been experiencing other similar products.
Advertisement

Data driving the content

NamnlösContent marketing has been a marketing approach where relevant and valuable content is used to entice customers. The better the content, more the customer engagement. But what if the companies are distributing content which is irrelevant to their customer base or targeting the wrong audience? The answer ofcourse is the most cliched word in modern times – data!

To get relevant, creative and engaging content out there to a targeted audience, strategic omni channel content marketing needs to be in place. It is imperative to optimize, analyze and curate content according to the brand image and customer demands. It is also equally important to hear the customer opinion in popular social media platforms, to be able to produce content that engages customers.

Optimizing content starts with analyzing content and the consumers of the content. There are innumerable web analytics tools that analyze web traffic. For example Xiti, Optimizely, Clicky, Google Analytics, Marketo and Hubspot to name a few, that can be used to reveal the content that attracts most influx. However, statistical programming languages like R and python are also widely used by data scientists to conduct advanced analytics. To be able to analyz how the content fairs in social media, data regarding the content outreach has to be organized by analyzing the number of likes, shares and comments. Both Twitter and Facebook provide APIs which can be used to extract valuable data to optimize content. For example, by analyzing the frequently used words associated with a particular brand, the sentiment associated with the brand can be determined. Competitive analysis can be carried out by comparing the sentiments associated with brands. Publishing houses are resorting to data journalism to put together related articles in the form of compelling story-telling. Data regarding the articles that attract most traffic at a given point of time is used by publishing houses to manipulate and push the most popular content in real time. Check how The Guardian uses data to narate associated and popular stories on its datablog.

The importance of using data is very significant in increasing the online traffic, however, nothing beats highly creative and engaging content

The data value chain

lifecycle
The Consumer Lifecycle

The terms “Data driven” and “Big Data” are the buzz words of today, hyped definitely, but the implications and potential are real and huge! Tapping into the enormous amount of data and associating this data from multiple sources creates a data chain, proving valueable for any organisation. Creating a data value chain consists of four parts: collection, storage, analysis, and implementation. With data storage getting cheaper, the volume and variety of data available to be exploited is increasing exponentially. But unless businesses ask the right questions and better understand the value that the data brings in and be sufficiently informed to make the right decisions, it does not help storing the data. For example, in marketing, organisations can gather data from multiple sources about acquiring a customer, about the customer’s purchasing behaviour, customer feedback on different social media, about the company’s inventory and logistics of product delivery. Analyzing this stored data can lead to substantial number of customers being retained.

A few of the actionable insights can be as follows:
  • Improving SEO (search engine optimization), increasing the visibility of the product site and attracting more customers
  • CRO (Conversion rate optimization) i.e. converting prospects into sales, by analzying the sales funnel. A typical sales funnel is Home page > search results page > product page > proposal generation and delivery > negotiation > checkout
  • Better inventory control systems, resulting in faster deliveries
  • Predicting products that a consumer might be interested in, from the vast inventory, by implementing good recommendation algorithms that scan through the consumer behaviour and can predict their preferences
  • If some of the above points are taken care of, customer loyalty can increase manifold, based on the overall experience during the entire consumer lifecycle.
actionable
Data blending which leads to a Single Customer View and Actionable Insights

Often the focus lies on the Big data technology rather than the business value of implementing big data projects. Data is revolutionising the way we do business. Organisations, today, are inundated with data. To be able to make sense of the data and create a value chain, there has to be starting point and the customer is a good starting point. The customer’s lifecycle with experiences at every touch point defines business growth, innovation and product development. The big data implementations allow blending data from multiple sources leading to a holistic single view of customer, which in turn gives rise to enlightening insights. The data pretaining to customer, from multiple sources, like CRM/ERP/Order Management/Logitics/Social/cookie trackers/Click traffic etc., should be stored, blended and analysed to gain useful actionable insights.

In order to be able to store the gigantic amount of data, organisations have to invest in robust big data technologies. The earlier BI technologies that we had do not support the new forms of data sources such as unstructured data and the huge volumes, variety & velocity of data. The big data architecture consists of the integration from the data sources, the data storage layer, the data processing layer where data exploration can be performed and/or topped with a data visualization layer. Both structured and unstructured data from various sources can be ingested into the big data platform, using Apache Sqoop or Apache Flume, real-time interactive analyses can be performed on massive data sets stored in HDFS or HBase using SQL with Impala, HIVE or using statistical programming language such as R. There are very good visualization tools, such as Pentaho, Datameer, Jaspersoft that can be integrated into the Hadoop ecosystem to get visual insights. Organisations can offload expensive datawarehouses to low cost and high storage enterprise big data technology.

bigdatarch
Edited image from Hortonworks

Irrespective of the technical implementation, business metrics such as increasing revenue, reducing operational costs and improving customer experience, should always be kept in mind. The manner in which the data is analyzed could create new business opportunites and transform businesses. Data is an asset and investing in a value chain, from gathering to analyzing, implementing, analyzing the implementations and evolving continuously, will result in huge business gains.

Streamlining the process of processing

simplifyThe customer expectations are very different, now. Decisions need to be taken in real time, to convert a prospective customer into committing. In an age, where customer seeks instant gratification, organisations that have a longer time-to-market due to cumbersome internal processes, customer loyalty is hard to win. For example, a customer visits your physical store, if you offer a discount at the very first visit, the chances that the customer will revisit your store are high. On the other hand, if you are merely noting customer behaviour which then has to pass through unwieldy processes, later, to mete out a discount coupon, the second time the customer visits your store… if at all, is a thing of the past. The advanced analytics systems now, are able to handle data influx from multiple disparate systems, cleanse and house in the dmp (data management platforms), ready to be queried in real time to cater to predictive and actionable insights, on the fly.

However, if the business methodologies used are not complimenting this speed of data processing, the business will still suffer. The widely used, Lean methodology preaches creating more value for customers with fewer resources. Anything that does not yield value should be eliminated. But organisations need to adapt to only the best of the best practices. Following methodologies by the book, on the contrary, causes bottlenecks. To be able to leverage more out of the Business Analytics systems and solutions, the processes and tools, both, need to be streamlined to create customer satisfaction. A lot of the business intelligence projects take too long to deliver and are inflexible, resulting in the functional business teams procuring BI tools which promise quick wins. The problem with such data discovery tools, apart from creating data silos, are that they lack data governance, hinder data sharing at an enterprise level and increase licensing costs.

It is not a solution to have no business process at all. There needs to be accountability and that comes from business processes. It is a continuous iterative process to find the right balance between processes and the speed of delivering value to keep the costs low and increase the profitability of any business. One size does not fit all and it applies to organisations, as well. Methodologies/processes need to be tweaked, tuned and tailor made for each company. Organisations that try to implement Lean/Agile/Scrum but fail are because they lose the customer focus, some companies do not have a clear strategy in place with employees being assigned foggy responsibilities and lack of communication and this in turn results in the focus shifting from the task at hand to the nitty gritties of such project management methods.

To avoid pitfalls, a clear business strategy needs to be defined specifying business goals in order to maximise gains. The next step is to trim all the processes that lead to this gain.