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Retail merchandising strategy is paramount for small and medium sized retailers to boost sales of their products. It’s imperative to explore every corner of business strategy landscape to survive tough competition. For example, determining the place where a particular type of product needs to be placed so that maximum prospective customers can see it with ease, which can be the difference between a sale and non-sale.

Retail merchandising involves:

  • Launching right product

  • Setting right price

  • Positioning Products at the right places

  • Placing products in right amount

  • Knowing types of customers buying a particular product

  • Drawing traffic to particular products

  • Improving customer relationship

  • Buying trend

The problem is that with all this, there comes a huge volume of disparate data, which is basically useless if one can’t run proper analytics on it to figure out sales patterns, optimum positioning and buying behaviours of customers and perhaps more importantly so, the prospects.

Use of analytic tools could do wonders for small and medium sized retailers. Many of them often struggle to come up with an effective merchandising strategy because of being deprived of information they can extract from their own databases, forget about the vast amount of useful data floating around on the interweb.

Social media, industry forecasts, existing customers records and web browsing patterns can help retailers predict products a specific segment of customers is more likely to buy. For example, Kohl’s had announced personalized offers for customers in five of its stores. Smartphones were all required for customers to opt for the offer while they visited one of those stores. A customer who had looked for a pair of shoes online but never went ahead with the purchase would receive a coupon based on the same shoes. This had increased the chances of the sale of the shoes for Kohl’s by many folds, as customers have a very high likelihood to avail an offer when they get it at the time of purchase while they are shopping.

With increasing use of the internet on cellphones worldwide, experts predict that 25% of the world will be soon on social network. This creates big opportunities, but simultaneously, it also creates problems owing to unstructured, semi-structured and muddled nature of data. Here pops up a question how to use big data to help small and medium retailers devise marketing strategies that improve customer experience, boost sales, understand buying trend inside a retail outlet etc.

But first, let’s get some concepts right about Big Data. Let’s start with the three Vs of big data - Volume, Velocity and Variety.

Volume - Nowadays, a lot of data is available in the form of videos, musics and large images on social media channels. The volume is so large that normal computer systems are incapable of processing it.

Velocity - Data movement has become very fast. Gone are the days when data of 24 hours ago was considered recent. Now, people don’t rely on newspapers to stay updated, they rather get the latest news through social media, which even tells you what happened half an hour ago. Updates are now made almost every second as data is being accumulated across the world on various platforms. This fast movement of data represents big data.

Variety - Data is available in many formats, like database, excel, csv or access.  It’s sometimes even available in the the form of video, SMS, pdf etc. It’s a big challenge with big data to arrange data available through different formats in one format.

IBM is among many companies that offer big data solutions to retailers to help them devise personalized marketing campaigns. IBM’s big data solution helps retailers understand customer shopping behavior, improve cross-selling & upselling, analyze product and customer data to avoid stock-outs and overstocks etc.

However, these full-fledged big data solutions are very expensive for small and medium sized retailers. The best remedy to reduce high costs of big data solutions is to go for customized solutions. Evon Technologies offers such custom-made big data solutions to retailers at very nominal prices, thereby providing them an affordable way to make their business more agile and robust. Having a tool to understand big data is next frontier for small and medium sized retailers in order to ensure their survival amid cut-throat competition.  


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A lot of songs have been sung about the virtues of having precise information at the precise time. And these songs just don’t get old. If anything, they are only getting BIG.

 

People are looking for information (read products and services) all across the web. You, as a salesperson might have an offering but the problem is - what are the chances that the person interested in it will find you and reach across to you? Frankly, the chances are quite less. So what do you do to increase your chances to make a sale? Well, obviously the best thing you can do is to find and reach across to that person before he decides to give his money to someone else. But how to do that? Traditional lead generation methods are only so effective as to give you an excuse of an alternate to shooting in the dark. The generated lead data is limited, the windows are short, the targets are big, the work is harder and the results are uncertain. The conversion rates can well be compared to the conversion rate of a toiling army of bees for one drop of honey.

 

Lead-Generation-Methods-1

A decade ago, most salespeople would agree that the traditional methods only took them so far in terms of conversion rates. The data was too limited or redundant and took too long to accumulate but the silver lining, if we can call it that, was that because it was too little, it was easy to process. You got 30 leads, you go and do your salesperson thing with 12 based on some quick prospecting/scoring and depending on how good or lucky you are, you score a couple.

 

Then five years ago to until recently, salespeople were agreeing that the contemporary methods with the power of web and social media, brought improved capabilities in data acquisition and reach but still something was keeping them from milking that cow. You’d think with all that talk about shrinking degrees of connection, businesses increasing their online presence and all, you’d be better off than mere 3% growth.

 

Conversion-Rates.jpg

 

Yes, something was definitely missing from the picture. And that something was to do with this - “Having access to a lot of data means nothing if you don’t have a way to utilise it...to its full potential.”

 Analytics-Requirements.jpg

Hmm…”utilizing”, people thought. And then they thought of newer ways to do that. New buzzwords started cropping up - Mining, BI, Analytics. But while that was happening, the data kept spawning silently, persistently and exponentially. And by the time the Sales teams settled on their Analytics tools, they found to their utter despair that they weren’t enough anymore to handle the Volume, Velocity and Variety of data that has been piling up all that while. That almost took the whole bang out from the so called data-explosion. Fortunately, that didn’t happen. Especially, in our case, for the Modern Salesperson.

 

The modern salesperson, despite having the same problems (perhaps even Bigger), are agreeing, either reluctantly or expectantly to one thing - that a major paradigm shift in the way information is produced and consumed has been set in motion for some time now, that there is an enthusing buzz in the air and that that buzz seems to hold a Big promise!

 

Big Data Promise and The Age of Proactiveness

 

There’s lots and lots of data floating around the web holding immense potential information for you as a sales person, if only it can be churned to your benefit somehow. But given the speed at which this data is getting generated and becoming obsolete, even the first step can become overwhelmingly discouraging. That first step is - to capture this huge amount of data in one place. But then, the tougher part comes next -  to make it sensible and actionable. For a salesperson, this sensible and actionable information is what he calls a Lead.

 

So how does Big Data help or proposes to help? Well to start with, Big Data Solutions solve this problem of getting you actionable leads by helping you with at least four things making your chances to conversion far better than those of that salesman a decade ago. These are:

 

Avoid Paradox.jpg

  • Identifying most valuable potential customers and creating windows of opportunities
  • Telling you the precise thing to show or say to them when the window opens
  • Have the right thing to offer at the right time to your prospect
  • Raising right flags at the right moment to generate cross-selling and/or up-selling opportunities 

 

 

Big Data Impact on Sales

 

Big-Data-Sales.png 

Companies collect a lot of data through a wide array of channels like mobile, website tracking/analytics tools, contact forms, social media, lists, groups & forums, CRM systems and news feeds. While big companies prefer to use their custom developed or customized Acquisition and Analytics solutions by Big Data solution providers like IBM (BigInsights), Cloudera and HortonWorks; most companies (SMBs mainly) prefer to source their data from a new breed of service providers falling under DaaS (Data as a Service) category who provide On-Demand industry-wise, rich, hard-to-find-data of personnel who can be potential clients. This data is then imported into organizations CRM systems from where the analytics and further lead nurturing process is taken up. Or some prefer to go for the simplest of the solutions - "Outsource" the whole lead generation process to companies like Technology Sales Leads (www.tslmarketing.com), let them deal with the grind and hope to get valuable leads.

 

HadoopAnyway, let’s take a moment to see how the actual data acquisition works in terms of Big Data in general. Well, it’s usually done using the combination of traditional, contemporary and modern methods using techniques like manual and/or automated web content mining, data scraping, searching, social media profiling and crowdsourcing. This data is usually in an unstructured form and is constantly fed and processed into what we call in Big-Data terminology as data-sets using technologies like Hadoop. 

 

 

However (can’t stress this enough), just acquiring a lot of data isn’t good enough, for the simple reason that due to its muddled and voluminous nature, it is of little value in itself. To make some sense out of it requires a lot of sifting through, filtering, consolidating, cleansing and validating. And because this effort requires time, using traditional (slower) approaches, it’s more prone to become counterproductive, especially in case of Sales because from Sales perspective, the long exercise might lead to generating more cold leads than any useful ones, as data keeps coming in and changing at a rapid rate and has the tendency to become obsolete fast.

 

So it becomes imperative to find a way to do it in a more efficient and productive way. One way to do it by having a tool or a system to do this crunching and churning for you - and giving you a streamlined and consolidated picture of what the above systems are feeding you with. But given the big volume of such acquired data, managing it and running complex analytics queries on it becomes a challenge with traditional RDBM systems. And that’s where the Big Data guys come in. Companies like Oracle, Cloudera, Hortonworks, IBM, Intel, Microsoft, and many others all have identified the potential of a solution to this Big Data problem and have come up with their own versions of Big Data Analytics solutions.

 

In our graphic, this whole thing is happening at stage 2.

 

Once you have the targeted leads, the usual Sales Process takes over, the only difference is that since the lead generation, prospecting and scoring has been mostly taken care of by the system, you as a Sales person hit the ground running armed with exact information of who to contact to, what to offer him and when.

Start Well to Finish Well 

 

One of the big advantage that these solutions offer is the range of Analytics one can perform over a large amount of data in a quick and visual (graphs, charts, tables) way. If we take our case of Big Data application vis a vis Sales Process, the direct implication is the shortening of the traditional long-tailed lead nurturing and lead scoring processes by doing the dirty mining work and handing over targeted insights based on your specific criteria (like industry vertical, company size, company revenue, location etc). This ultimately allows a Salesperson to filter out the weak leads and focus on nurturing only the valuable leads (graphic: Stage 7), the ones which have the greatest chance of conversion to Actual Sales.

 

The beauty of the system is that at every step, new transactional data (financial, logistical, communications etc) is getting generated and getting fed-back into the system which in turn helps in the process of generating repeat, cross-selling and/or up-selling opportunities. Talk of eating your cake and having it too!

 


 

Evon Technologies is a software consultancy based in India and has performed Proof of Concepts for data mining companies with Data-Integration and Hadoop Analytics requirements.

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Here, in this blog, I would like to tell you why marketing of a product should start when its development starts. I am sure, you may think what is the need to market any product at its pre-mature stage. You may also think it is the stupid idea ever because the idea can be leaked or copied, but, let me tell you friends that it is the best idea to start marketing any product when its development starts.

 

Well, nowadays, entrepreneurs are more focused on marketing products from their initial stage. The agenda of marketing a product at its initial stage is only to provide awareness. Give a brief description of your product and explain its benefits.

Why do now than later?

  • He did not like the flow! I can't recode that again.
We built our product/website/app with our own seed idea, however different perspectives and views always help to improve the product idea. By involving your social and professional network along with potential customers early in the product development lifecycle, you not only improve the chances of success but also reduce the time required for taking the product from inception to release in the market. Hence, the key is to develop the product iteratively with an inbuilt mechanism of Customer Feedback early in the development lifecycle.
 
  • I have launched the product on 10 January and I have 1000 users on 16 January.
The above statement impresses the investors the most. Marketing takes as long as building a product. Today just results are not important but, quick results are. Your early marketing will give you a seed user base which is most important.
 
Hence, the two important keywords are, “Early Feedback” and “Seed User Base or Clients”.
 
Also, we would like to emphasize on early development of marketing plan. Marketing of a product is not something that strikes your mind when you are taking a shower, rather a proper planning and research is required to develop any idea. The marketing plan has to be clear and target oriented. It should strike the audience directly, then only it will work.
 
The marketing ideas can be generated with the help of family and friends' reviews. Involving and sharing the ideas of both old and new generations bring experiences and modernity respectively that help you evolve a new idea. To start a marketing plan, one should follow some simple rules.
 

Sell yourself and your product from the start:

  • Social media, YouTube and various other promotional sites will help you to promote the product. Promotion is not only free on these sites, but also fast & easy. In the previous era, to promote any product entrepreneurs not only indulge their money in its development, but also in the promotion. But now, because of these social media sites, promotion is advanced and free. Create your videos explaining the idea and tell about yourself why this idea can be best implemented by you.
  • Create noise, be loud; this can be done by sharing your idea, as simple as you share the logo of your product on the Social Media with your friends and family. The likes and comments will not only encourage you but also help you to know whether this idea is fruitful or not. Reach is important!
  • Conduct the SWOT analysis in order to identify the strengths, weaknesses, opportunities and threats of the existing market. This will keep you connected with the changing market situations and enable you to take decision what to be done next.
  • Use more target oriented search for companies which specialize in giving a launch platform to startups and bring your idea into reality.

 

Choose the marketing options like, Social Media & Print Media and, step by step walk along through the things you have done for developing a product. Treat your product like a baby, and let the world know what all efforts you made to bring your product into maturity.

Just to give you some initial steps you should do:

  • Create Twitter, Google, LinkedIn and Facebook page for your product and promote it on these websites.
  • This page should be like your daily journal. Your frustrations, your happiness everything should be recorded.
  • Ask your friends and family to follow that page.
  • Create a simple blog, with the product user stories.
  • Share, Share, Share. Let ideas come in.

 

At the end, I would like to say, our company, Evon Technologies has a dedicated team focused on digital marketing of the products we build for our customers as well as our in-house products.

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