3 items tagged "sales"

  • 5 Arguments that will convince sales people of the value of analytics

    5 Arguments that will convince sales people of the value of analytics

    Many sales reps have a certain way of doing things. Implementing new processes or adding new tools or technologies that attempt to change their habits can often be met with resistance.

    Sales reps rely on their “tried-and-true” methods learned from predecessors, or they lean on their personal knowledge and experience to manage their customers and plan their approach with individual customers. Gut-feel has been the leading driver for sales strategies for many years, but in today’s fast paced and competitive environment, sales reps need every advantage they can get.  

    A recent McKinsey article suggested, “driving sales growth today requires fundamentally different ways of working, as well as outstanding execution across large, decentralized sales teams and channel partners. While many sales leaders accept this reality in principle, they don’t put sufficient energy or focus into driving that level of change. Advances in digital and analytics, however, mean that sales leaders can now drive and scale meaningful changes that pay off today and tomorrow.”

    So, if you’re a sales rep that doesn’t think you need data analytics, here are five reasons why you do:

    1. There are always more sales opportunities than you think 

    This alone should steer your team toward data analytics. Data can uncover trends in your customers’ buying behavior that can help you identify gaps in their ordering. In addition, your customers’ data can also reveal upsell or cross-sell opportunities that can help you increase your sales volume across a much wider swath of products, without impacting any of your existing sales. While your gut feel may tell you to spend more time with a customer, data can help you understand why, pointing you to new complementary products that can quickly grow your sales.

    2. It is critical to uncover challenges before they impact your bottom line

    There is a good chance one or more of your customers purchase products from other suppliers. What if that same customer started to buy less from you and more from that other supplier that recently entered the market? What if that decline occurred over several months? Would you even know? These are difficult questions to ask and answer, but if you’re like many sales people, you have dozens of customers that you are working with and a slow decline in sales with a single customer may go unnoticed. With data at your fingertips, from your laptop to your mobile device, you can constantly monitor your customers' purchasing habits, and ask questions about negative trends before they start to impact your company’s bottom line and your paycheck.

    3. Retaining customers is easier than finding new ones

    This is related to number two, but it deserves its own bullet point. Retention is a simple business reality that makes your business data even more important. Underserved customers are underserved for a variety of reasons. Perhaps they are new and got lost in the shuffle, or turnover at the sales rep position has left them without support for a period of time. Perhaps they have made several large purchases over the last year and deserve better pricing, or they were once a loyal customer, but their sales have slowly declined, and are at risk of leaving to a competitor. Engaging these at-risk customers requires that you recognize the signs before they take their business elsewhere.

    4. It will make your life easier 

    Access to data analytics has oftentimes only been given to the IT team or specially trained individuals. Data analytics turns raw data into actionable intelligence. No more reading outdated spreadsheets, guessing where your next sale will come from or what information to share with your customer during your next sales meeting. Business intelligence software is designed to help you quickly mine value from data so you can make the right decision for you and your customers. Rows and columns of data are now presented in charts, graphs and tables that you can click to uncover transactional level details that brings to the surface the accounts that need your attention the most. Data analytics helps you eliminate the guess work about your job and focus on what customer you can help the most while also helping you achieve your sales goals.

    5. It helps you prepare to perform

    Imagine going into a customer meeting with their entire order history at your fingertips, or an understanding of their recent commitment to certain brand, style or size of product. How will that information shape your next product presentation or sales proposal? You can turn your customers into data advocates by reviewing with them weekly reports about their engagement with you. Could that information help them improve efficiencies, capitalize on sales promotions or recognize holes in their own ordering? As you share and use your data to help them, you show them that you are committed to their success, as well as your own.

    Data analytics is a powerful tool for sales people that are looking to maximize their performance, grow sales and retain customers. The results of implementing analytics are better revenue growth at the same or improved margins, quickly, while customer satisfaction improves. If you’re not using data to drive your business, there’s no better time than the present to start.

    Source: Phocas Software

  • Growth Stories: Change Everything

    mobile-uiInterview by Alastair Dryburgh

    What do you do with a small technology company which has an interesting product but is stuck in a crowded, noisy market where larger competitors have locked up many of the distribution channels? You could keep struggling on, or you could make a bold move; re-engineer the product to meet a different purpose for a different market. That's what Pentaho did, leading to 6-times growth over 5 years and a successful sale to a large organisation.

    In this interview their CEO Quentin Gallivan describes how they did it.

    Alastair Dryburgh: Quentin, welcome. This series is about that period of a company's evolution when it has to go through the rather dangerous territory that lies between being and exciting new start up and being an established profitable business. I'm told that you've got a very, very interesting story to tell about that with Pentaho. I'm looking forward to hearing that.

    Quentin Gallivan: Okay, great.

    Dryburgh: What would be useful would be if you could give us a very quick background sketch of Pentaho. What it does and how it's evolved in the last few years.

    Gallivan: So Pentaho, the company is approximately 12 years old. There were five founders, and they all came from a business intelligence technology background. What they were looking for was a different way to innovate around the business intelligence market place.

    One of the things I saw going on with that company was that the biggest challenge in companies doing data mining or predictive analytics on unstructured data or big data, was how do you get all this unstructured data, and unstructured data being clickstream data from websites, or weather data, or now what's very popular is machine data from Internet of Things devices.

    I wondered, is there a company out there that can actually make it easier to get all this different data into these big data analytical platforms? Because that was the biggest problem we had.

    When I looked at Pentaho, at the time it was not that company. It was not the new, sexy, next generation company, but I knew the venture capitalist behind Pentaho. We spent about a month just talking about what could the company be. Version one of the company was really a business analytics software product sold to the mid-market. They got some initial traction there, but that was a very cluttered market - very busy, a lot of noise, lots of large incumbents with channel dominance and then lots of small companies. It was hard to get above the din. I was not interested in Pentaho as the company was, right? I didn't see that as very interesting, very compelling.

    What interested me though, was when you dug deeper on the technology I thought it could be repurposed to address the big data problem. That was a big leap of faith, right? Because at the time, Pentaho wasn't doing any big data, didn't have any big data capabilities. The customers were all mid-market, small companies and it was known as a business intelligence company.

    Dryburgh: Pretty substantial change of vision really, isn't it?

    Gallivan: Massive, massive change, and I looked at it and I spoke to the VC's and said, "I would be interested in taking the CEO role, but not for the company that you've invested in, but for a very, very different company and I think we can do it. I don't know if we're going to do it. It's a long shot, but if you're willing to bankroll me, and allow me to build a team and support the vision, I'll give it a go."

    Dryburgh: Could I stop you there a moment to see if I could put a little bit of a frame around this? You've got a pretty fundamental change here.There's probably, very crudely, three different elements you've got to look after. First is obviously the technology and I guess that must have needed to evolve and develop. Then you've got what you might call the harder side of the organisational change, the strategy, definition of who the customer is, the organisation, the roles, the people you need, that's the second one. Then the third element which I think is particularly interesting is the softer side which is the culture. I'd be really interested to hear which of those was the biggest issue for you?

    Gallivan: That's a great question. I like the way you framed it, I would add a fourth dimension, which is the market perception of you. How do you get people to stop thinking about you as Open Source BI company for small and medium size businesses and think about you as leading, big data analytics platform for a large companies, for the large enterprise. Those are the four vectors that we needed to cross that chasm.

    The hardest one was not the culture because at the time, the company was very small. It had 75 employees and we are going to be over 500 employees this year, right? At the time it was really an open book from a culture... The founders were very open to a change in the business. For most startups, less than 100 employees, the culture is generally driven by the founder or founders and so there was no resistance.

    Dryburgh: Okay, good. So what were the biggest things you had to do to make the transformation work?

    Gallivan: If you look at those, just think about the transformation in those four key areas, you look at the metrics. Five years ago we were known as a commercial open source BI company selling to midsize companies. What we wanted to do was to be known as a big data analytics company selling to large enterprises because for big data that's where the dollars are being spent right now.. What we did was we set down the mission, we set down the strategy and then the other piece, and this is sort of from my GE days when it comes to strategic execution, that we employed was you've got to have metrics that drive milestones in the journey.

    What we started to do was we tracked what percentage of our business came from mid-sized small companies versus large. Five years ago 0% came from large. Last quarter it was 75%. Then over this journey we would track that percentage of our business that came from these larger enterprises. The other thing we would track was in that fourth vector, the brand. How do you change the brand from being known as an open source BI company to being known as a big data analytics company? There we had again, at the best marketing organisation I've ever worked with that had a share of a voice metric. Not a feel-good, hey we had so many press releases, but a quantifiable metric about our brand that we tracked four years ago and it was what position do we play and what share of voice do we have when people talk about big data versus non big data.

    That was where our marketing team was very aggressive and had these metrics. When we first started out, since we launched ourselves as a big data analytics company we had a pretty good penetration in terms of the brand, but over the last couple years we've been tracking, we've been number one or two versus our competitors as the most identifiable brand in big data. That's a metric we track every month. Very, very quantifiable, but it's part of the journey. It took us a while to get there.

    Then the other piece, the other key metric for us is really the R and D investment and that was, we basically had to transform or re-engineer the project to really meet the needs of the large enterprise from a security standpoint, a scalability standpoint. Making sure that we integrate with all the key technologies that the large enterprise have and so that was again, when we did prioritization around out R and D we would prioritize and we'd have metrics around large enterprise and then we would sacrifice the needs of the small/medium in the product road map. That again was an evolution.

    Five years ago 10% of our R and D investment went into large enterprise features. Now that's the majority, it's something didn't happen overnight but we tracked and we shared with the company and sort of made it work.

  • Why investing in MI is key to your sales performance

    Why investing in MI is key to your sales performance

    In the age of data, choosing not to invest in a quality market intelligence (MI) solution can mean your sales team is losing market share to your competitors. More companies are investing in MI than ever before. These companies are achieving a significant advantage over those who are not using market intelligence solutions.  In today’s blog, we will discuss a few key ways in which the choice not to use MI can kill your sales.

    Without MI you do not know which customers you are losing

    Sales managers typically have at least one rep who reports to them. These reps often sell a wide variety of products and can work long hours. It can be difficult for a rep to detect when a customer has partially decreased their order volume over time, or gradually stops buying one product but not another.

    Oftentimes, this insight is discovered by chance. For instance, a colleague in another team or department may remark that a customer hasn’t ordered a particular product lately. In this case, proactive management to retain this customer gives way to chance. This can have a substantial impact on your overall sales figures.

    Because MI provides you with a clear picture of your customers’ buying patterns, your team can quickly detect any decrease in order volumes. With this knowledge, your team is empowered to respond proactively to the situation by sending in a rep before any major damage is done. 

    For instance, the customer may have negotiated with another vendor for a lower price or shorter lead time. By catching this problem at the front end, you can quickly intervene to re-negotiate better terms. This, in turn, may enhance your relationship with this customer as they now know they can come to you first before negotiating with another vendor in the future. Interestingly, 95% of customers don’t raise concerns before they stop buying. Having an open dialogue with your customers may minimize this issue.

    Without MI it is more difficult to discover new sales opportunities

    Increasing the number of products you sell to existing customers can be an easy way to boost revenue. That is, as long as you have MI. Without MI,cross- and up-selling are reliant on your sales reps and their personal assessment of your customers’ needs. For instance, a customer may be buying a product but not a complimentary product such as pasta but no sauce. In this case, the customer is purchasing that product elsewhere. An experienced rep may have fine-tuned their gut-instincts to recognize the bigger picture, but hunches and instincts are based on human interpretation, not fact.

    With MI you can easily see which customer is buying product A, but not product B, and respond by sending in a sales rep to make the sale. With MI, you are also able to identify the purchasing trends of similar customers.  With this information, you can quickly detect new sales opportunities. For example, a customer may benefit from being offered a line of more luxurious products. Another may be interested to in learning about a new product their competitors are buying. With the power of MI, you can become an advocate for your customers’ experience and business success.

    Without MI, preparing for a meeting with a customer is time-consuming

    Without the benefit of timely and accurate reports generated by MI, it is difficult to gain true insights into a customer’s buying patterns or to uncover sales opportunities. In this case, sales reps and leaders are reliant on traditional reporting through the IT team. Because these reports can take several days to reach your desk, the data is often outdated. And due to their static nature, these reports provide no opportunity to query the data to discover the underlying reasons for the trends you’re seeing.

    While some sales meetings do allow for this amount of pre-planning, chances are many do not. In reality, spending time to have reports generated and then examined before meeting with a customer is something not all sales professionals can afford. From a business point of view, even if your sales team is capable of getting the reports, consider all the time and effort involved. Time is an expense. 

    With access to a quality MI tool, your sales reps have a clear profile of each customer and their buying trends. 

    Not only does MI help to improve overall sales performance, it may also reduce the long hours and stress of your individual sales reps. Happier reps may create a happier work environment.

    If you're looking for a reliable MI partner, be sure to check out Hammer Market Intelligence.

    Source: Phocas Software

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