Mobile communications optimization service. Optimization of communication systems: costs for the operator or an economically justified need? What does cellular communication optimization give an operator?
23.05.2016
The goal of any operator is to provide its customers with coverage and services of higher quality than its competitors. A stable signal anywhere in the city, high data transfer speeds and a large package of services are one of the main ways to attract new customers and increase profits.
If you conduct a more in-depth analysis of the situation, you can discover other factors that influence the increase in operator profitability. These include a significant reduction in network maintenance costs, minimizing risks and ensuring uninterrupted operation of the entire system.
But any, even minor, increase in operator efficiency is preceded by long-term preparation. Optimization of communication networks begins with an audit and analysis of their current state, and for this, operators attract outsourcing companies.
What does an audit of communication services include?
The exact list of work is determined by the final goals that the operator needs to achieve: modernize the network, improve the quality of coverage in a specific area, etc. As a rule, companies providing such services to operators are able to perform research of any complexity.
We turned to the Modern Communication Technologies company, which has experience working with federal operators. According to management, the company has innovative equipment and a large suite of software for data analysis. Thanks to this, optimization of communication systems is carried out as efficiently as possible, since the operator receives objective information on a huge number of parameters.
During network exploration, the following can be performed:
benchmarking, or comparative assessment of several operators;
analysis of customer statistics;
configuration analysis (an audit of objects in sectors is carried out, heights, azimuths, inclination angles, etc. are measured);
verification of frequency-territorial plans;
The last point implies a whole range of field research. Based on the results obtained, measures to improve the quality of voice and data transmission are subsequently developed. Among the main measured parameters:
- parameters of availability, retention of voice services;
- parameters of radio channels;
- Location Update;
- MeanOptionScore;
- data transfer rate;
- quality of radio coverage in UMTS, LTE, GSM standards.
Cellular Optimization
After receiving a large volume of measurement results, they are processed using specialized software. The Modern Communication Technologies company uses the products Anite Nemo Analyzer, Actix, Ascom Tems Discovery. All programs allow maximum visualization of information in the report, thanks to which the operator receives a clear picture of the network status.
Technical optimization of communication networks allows the operator company to use available resources more efficiently, reduce system support costs, and solve many internal problems. In addition, the quality of the services provided is noticeably improved, which makes it possible to attract new subscribers and retain existing ones.
1.3 OPTIMIZATION BLOCKS
As already noted in Chap. 2, the algorithmic complexity of the problem of synthesizing communication networks is such that exact methods for solving it using mathematical programming are practically inapplicable. The main difficulties in designing distributed communication networks are caused by the following reasons:
significant dimensions of the designed networks (for example, the problem of optimizing a telephone communication network based on the cost criterion can be reduced to a discrete nonlinear programming problem, but the dimensions of the actual designed networks are such that the direct use of methods for solving nonlinear problems in the general case becomes impossible);
the complexity of a complete mathematical description of the network, which necessitates a number of significant restrictions on the synthesis problem.
The main limitations of the synthesis problem include: the assumption of the stationarity of the technical base of the network and its parameters, the assumption of the stationarity of control procedures and the statistical equilibrium of network processes, the assumption of the Poisson nature of the flow of requests, the exponential nature of the distribution of discrete message lengths and the time the channel is occupied by a telephone message, the assumption of there is no possibility of interrupting the transmission and no time wasted searching for the path to transmit the message. For telephone networks with circuit switching, the Poisson character of the missed and excess load is assumed, the absence of internal blocking in switching nodes and the absence of repeated requests for service; for networks with message and packet switching - the absence of interdependence of the delay times of a given message (packet) in different queues, the absence of dependence the delay time of the message (packet) in the node and the time of subsequent transmission over the channel; it is assumed that the message (packet) does not have a fixed length and at each transit node it is assigned a new length, etc. Naturally, the acceptance of restrictions determines the approximate nature of the calculation;
the need for an integer solution caused by the discrete nature of a number of technical means;
nonlinearity of the cost functions of network elements, which necessitates their approximations, solving the problem at the level of approximating functions and choosing a solution to the problem by discretizing continuous functions,
In connection with the above methodologically justified rule for solving the problem of communication network synthesis at present, a combination of a set of heuristic procedures for optimizing the solution of particular synthesis problems with the involvement of elements of statistical modeling is presented. Note that, despite the approximate nature of heuristic algorithms for constructing communication networks, the use of heuristic optimization procedures makes it possible to reduce the costs of the designed communication network by approximately 30%.
Since the solution to the general problem of synthesizing a communication network must consist of a set of procedures for solving particular problems, it seems appropriate to study a set of particular design problems in order to determine the possibility of their autonomous consideration and determine the best sequence of their application.
Let us consider the problem of synthesizing a switched communication network. We assume that the following data is known:
structure G(V, U) primary network, where V- many switching nodes of the network; U- many network communication lines;
matrix Y=|| || loads, characteristics of application flows, priority structure;
matrix S=|| || rental fee for using a unit of bandwidth (channel) between nodes i, , and Sij- step function of distance, independent of i, j;
probabilities (q(i),q (u)) node and communication line failures. ;
probabilities (P()) emergency or intentional simultaneous damage to n1, nodes and m1 communication lines.
We will assume that the requirements that the synthesized network must satisfy are known;
matrices 
acceptable losses (delays);
matrices of permissible losses (delays) with simultaneous failure of n1 nodes and m1 communication lines;
limitation l for the maximum number of transits (receptions) when transmitting information between each pair of network nodes;
restrictions ω(λ) on the number of paths independent along vertices (edges) between each pair of nodes of the synthesized network (restrictions l,ω,λ, may naturally arise when trying to provide the required quality of service).
When synthesizing a communication network, it is necessary to determine: the network structure (network graph), channel capacities of network communication lines, switching and cross-connect requirements for network nodes, required storage capacities at network nodes (for networks with packet switching and message switching);
communication network management graph with the definition of private algorithms for monitoring and managing (and their interdependence) the structure (resources) and network load, distribution and transmission of information over the network, including path selection algorithms and request servicing disciplines.
As a criterion for optimal synthesis of a communication network, we will take the rent for the total channel capacity of the network’s communication lines in the absence of restrictions on the capacity of the lines.
We will consider the synthesis problem under the following assumptions: assuming a stationary flow of service requests; assuming there are no load priorities; assuming a constant (not scheduled or on demand) lease of primary network channels; under the assumption that the channel capacity of communication lines, switching and crossing capabilities of primary network nodes are sufficient to service the imposed load with the required quality of service.
Analysis of the problem of synthesizing distributed communication networks allows us to identify the following main particular design tasks:
GS - generation of initial network structures for the subsequent stage of local optimization. The initial data of the GS is the number n nodes of the synthesized network and requirements for the hierarchy of the network, the result is a certain network graph on n vertices, satisfying the requirements for hierarchy. As a rule, without taking into account the requirements for hierarchy, the minimum is accepted as the initial structure (in terms of distances, in terms of cost, when taking into account the load Y) spanning tree, star graph, complete graph, empty graph, graph whose edges correspond to non-zero matrix values Y, etc.;
AW—network analysis for connectivity by parameter ω or λ (choice ω or λ determined by the conditions of the synthesis problem). In general, an analysis is required for any required reliability indicator;
Ad- network analysis for metric property (maximum number of hops);
CW- network synthesis according to the parameter ω or λ . The analysis and synthesis of graphs with a degree of connectivity greater than three is not of practical interest, which is explained by the capabilities of control systems to select paths for transmitting information;
Cd- network synthesis by parameter d;
RP- flow distribution over the communication network. To reduce the implementation time of the RP stage, it is advisable to use heuristic distribution procedures. It should also be taken into account that the network capacity depends mainly on the total volume of flow in the network and to a lesser extent depends on the nature of the flow distribution throughout the network;
PC- calculation of network channel capacities to ensure a given quality of service for network subscribers.
When using methods for replacing (deleting, adding) branches, the following steps are required:
VK- selection of a candidate branch for replacement in accordance with a certain replacement criterion;
ZV- actual replacement (deletion, addition) of a branch.
One of the most important stages in the synthesis of a switched communication network is SU - statistical modeling of the process of network functioning under various laws of communication network control. Currently, there are no methods for calculating a communication network that are adaptive to the laws of managing its resources and load. Moreover, there are no general methods for calculating network channel capacities for arbitrary procedures for selecting information transmission paths. In this regard, simulation programs that make it possible to determine the quality of service indicators for communication network subscribers under various control laws and procedures for selecting information transmission paths are of significant interest. These include, for example, programs for simulating the relief method, simulating a game method for choosing a connecting path, simulating isorhythmic network control, simulating static and dynamic path selection strategies (programs simulate a packet switching network), etc. Programs for statistical assessment of quality of service, as a rule , determine only the integral quality indicator, since to calculate with equal accuracy all differentiated quality criteria, the simulation time, determined by the necessary statistics for a minimum intensity flow, is too long. In this regard, the already mentioned programs have become widespread AC- analysis of the communication network, allowing to calculate differentiated indicators of quality of service.
In general, the procedure PC, SU And AC are objectively aimed at solving the same problem - establishing correspondence between the required indicators of the quality of service of subscribers of the communication network and network parameters (structural and channel), and the first execution of the procedure PC precedes the first execution of procedures SU, AS(during the iterative design process, procedures may be repeated). Taking into account the design costs, it seems advisable to execute the sequence PC, AC or PC, SU as the final stage of each iterative design step and sequence PC And SU) as the final stage of the last design step.
The noted procedures are, apparently, the main procedures for the synthesis of communication networks (the issue of “functional completeness” of the presented set of procedures is of independent interest and is not considered here). Auxiliary synthesis procedures include procedures such as approximating cost functions, calculating network costs, checking the number of iteration steps, etc.
Naturally, different sequences of design procedures are possible, but given that HS- initial procedure, SU“alternative” to AS, SV immediately follows. VK. procedure CW(Cd) preceded by a procedure AW(Ad), procedure PC- procedures RP, Ad, Cd, procedure SU (AS) - AW, CW, PC, the number of possible sequences of procedures is significantly reduced.
Assuming that:
the process of synthesizing a communication network is a step-by-step iterative procedure, and the number of design steps is equal to the number of initial network structures, and the number of iterations in each step is either determined in advance or depends on the result of comparing the costs of network options [iterations are stopped if the cost of the network option is i-th iteration step is greater than the cost of the option; networks on (i-1)th step];
subsequence Ad, Cd, related to the distribution of flows across individual and common bundles of communication network channels must be performed after the RP procedure;
the branch replacement procedure is performed at the end of each iteration (taking into account that the procedures CW, Cd are essentially replacement procedures - in these cases additions);
the SU or AS procedure is performed at each iteration; CS and AS procedures are jointly performed at the end of each design step;
The most appropriate sequence of synthesis procedures is presented in Fig. 3.1, where C is the procedure for representing the structure
communication networks, “cost” - the procedure for calculating the total cost of channel capacities of the communication network, 1 - counter of the number of iterations, 2 - counter of the number of initial network structures. Sequence place A W, CW immediately before the RP or immediately after the PC is determined by the type of structure variant presented. Limiting cases: if WITH- tree, then AW, CW follows C, if C is a complete graph, then A W, CW follows PC. In accordance with the proposed synthesis methodology, the main design procedures are the procedures GS, AW, CW, RP, Ad, Cd, PC, AS, SU And ZV.
As the practice of designing distributed non-hierarchical communication networks of large dimension shows, choosing a local optimization stage as the initial structure - the structure of a minimal spanning tree or a star graph - leads to a very suboptimal final network structure. This is explained by the fact that such a choice of the initial network structure imposes very significant restrictions on subsequent optimization stages, and in the general case these restrictions are not justified. On the other hand, the choice of the second limiting version of the initial network structure - a complete graph - for high-dimensional networks is unacceptable due to the huge amount of necessary calculations. In addition, the two noted limiting options for the initial network structure almost do not take into account the nature of the load graph required for implementation G(Y): the complete graph provides direct bundles of channels to all requirements for information transmission; the minimal tree version does not allow the possibility of distributing streams of transmitted information along various transmission paths.
In connection with the above, the most appropriate option for the initial network structure when synthesizing a high-dimensional distributed communication network is the structure of the load graph (a minimal tree, a star graph and a complete graph can be considered as the initial structures of centralized networks or as the initial structures of small-dimensional distributed networks). Since the rent for channel-kilometers of the network is taken as a criterion for the optimality of network synthesis, applying all procedures of the local optimization stage directly to the graph G(Y) or to structures derived from G(Y), is correct. In some cases the graph G(Y) it is advisable to replace it with the graph G(Y\ε) obtained from G(Y) by removing edges connecting vertices with a mutual load less than ε *.
When considering the graph G(Y)(G(Y\ε)) as the initial structure of the distributed communication network design process
*) Since the graph G(Y) for general purpose communication networks is, as a rule, fully connected, its transformation into the graph G(Y\ε) is necessary.
The sequence of network synthesis procedures is represented by the diagram in Fig. 3.2 [here: G(Y)- initial structure].
Assuming the presence of AC programs (network analysis) and SU ( simulation modeling of flow distribution) and selection of candidate branches for replacement based on the results of the procedures AS, SU
the definition of the local optimization process consists in the selection of procedure algorithms AW, CW, Ad, Cd and PC. Let's consider some options for solving this problem.
NETWORK ZONING
In general, the solution to the problem of synthesizing distributed networks
connections using branch replacement methods (procedures CW, Cd, RP, ZV) requires 0(n 3)-O(n 6) calculations, where n is the number of network nodes, and for networks in which the number of nodes exceeds several hundred, it is not possible. One of the possible ways to reduce the complexity of design is to represent the synthesized large network as a collection of smaller networks (zones) and reduce the solution to the problem of synthesizing a large network to solving the problem of synthesizing networks and its components (zonal and interzone networks). The second reason for the advisability of partitioning (zoning) of a communication network is the need to allocate communication network management zones with localization of monitoring and control information within each zone.
If the desire to reduce the amount of design requires performing the network zoning procedure by structure as a preliminary procedure at the stage of its local optimization, then the network zoning procedure by control is performed, as a rule, after synthesizing the network structure.
The network zoning stage includes the solution of two main issues - determining the number of zones (partition blocks) of the network and choosing the principles for grouping nodes into zones, and solving these issues is most difficult for networks of a non-hierarchical structure. In the case of network zoning for management, the number of partitioning blocks generally depends on the network structure and the volume of the transmitted message flow, accepted management principles, performance characteristics of hardware and software management tools, etc. Currently, there is no general methodology for dividing a network into management zones. The optimal choice of the number of control zones remains open. At the same time, the option of enumerating the number of possible zones should not be excluded (due to the one-time nature of solving the zoning problem and the small size of enumeration).
Number Nc blocks of network partitioning by structure are selected based on the minimum design volume and are defined as , where n- the total number of nodes of the synthesized network;
Number of central nodes in each zone. The network is built as a collection Nc zone networks and an interzone network on , nodes (if we assume the same number of central nodes in each zone). If we assume that each zone network has only one central node, and this is usually true for lightly loaded networks, then Nc = .
Determining the principles for grouping network nodes into zones in the general case is associated with issues of estimating the cost and capacity of communication lines, with the tasks of distributing traffic throughout the network and ensuring structural reliability. The lack of theoretical results on the problem of grouping necessitates the search for heuristic principles of grouping. The natural principle of grouping is the requirement for minimal information connectivity both between management zones and between structural zones, since such a grouping quite correctly localizes management and structural synthesis tasks and allows minimizing the cost of the interzone network and interzone management.
The advisability of using the graph has already been noted above G(Y)(G(Y\ε)) as the initial structure of the process of local optimization of the communication network. Since the weights of the graph edges G(Y)(G(Y\ε)) equal to the information gravity between the corresponding network nodes, the expediency of its use (with the chosen grouping principle) is quite obvious and as a graph of the network structure for zoning (cutting).
The graph cutting problem belongs to the class of extremal combinatorial problems, i.e. problems in which it is necessary to determine the minimum (maximum) of some function F, defined on the totality
The quality of operation of information transmission systems is characterized by a combination of a large number of indicators, the main of which are noise immunity, speed, throughput, range, electromagnetic compatibility, weight and dimensions of equipment, cost, and environmental compatibility.
The set of system quality indicators can be written as a vector
The best (optimal) system is considered to be one that corresponds to the largest (smallest) value of a certain function
from private quality indicators The value is called efficiency or a general indicator of the quality of the system, and the function is the target function of the system (quality criterion).
One of the central points of the methodology for optimal design or comparison of systems is the formation of efficiency assessments - the target functions of the system. Such assessments are absolutely necessary in system studies related to such tasks as choosing the best system from among existing ones, assessing the level of system development in relation to modern world standards, determining the optimal version of a new (designed) system, etc.
In the simplest cases, the efficiency of systems is assessed by individual most significant parameters, for example, speed, channel bandwidth, signal-to-noise ratio, etc.
In general, a systematic approach is required, in which efficiency is assessed as a whole based on a set of parameters. In this case, first of all, it is necessary to take into account all the most essential parameters of the systems. The desire to take into account all parameters, including small and secondary ones, leads to a complication of the target function (quality criterion) and makes the assessment results difficult to see. At the same time, excessively limiting the number of parameters taken into account may lead to the criterion being too rough.
Any assessment of the effectiveness of systems is carried out with the aim of making a certain decision. Thus, during design it is necessary to determine the set of system parameters at which the greatest efficiency is achieved.
Quantitative assessment of effectiveness must satisfy certain requirements. It must sufficiently fully characterize the system as a whole and have a clear physical meaning and have the necessary flexibility and versatility. Evaluation of the effectiveness of the system should be
constructive - suitable for both analysis and synthesis of systems. Finally, the performance measure must be simple enough to calculate and easy to use in practice. A common method is to evaluate efficiency in the form of a linear function
where is the number of parameters (indicators) taken into account; weighting coefficients; - relative values of the parameters taken into account.
With this definition of the parameters included in the sum (11.27), the value can be determined in the range from 0 to 1. The best system will be the one for which the value is larger.
The choice of weighting coefficients X is, to a certain extent, arbitrary. The same applies to the number of parameters taken into account. However, the share of arbitrariness can be brought to a minimum by developing a rational methodology for finding these coefficients (for example, the methodology of expert assessments). The absolute values of the weights are not important; Only the relative weights are significant.
Modern complex communication systems cannot always be comprehensively characterized by one single indicator. An assessment based on several indicators can be more complete and at the same time more substantive, allowing one to characterize various properties of the system. It is clear that a large number of indicators is unacceptable. It is necessary to have several indicators characterizing the main most essential properties of the system: informational, technical, economic, etc. In many cases, it is enough to limit ourselves to two indicators, for example, noise immunity and transmission speed, frequency and energy efficiency, technical effect and costs.
The final decision, as a rule, is based not only on quantitative calculation data, but also on experience, intuition and other heuristic categories, as well as on additional considerations that could not be taken into account when constructing a mathematical model.
In the general case, the problem of optimizing the SPI is reduced to finding the maximum of the objective function when the system (its structure or the values of its parameters) varies, taking into account the initial data and restrictions on the structure and parameters of the system.
If the objective function is given and the set of admissible systems (or their variants) is determined, then optimization is reduced to the problem of discrete selection from a finite number of given systems, i.e. to choosing a system that corresponds to the largest (smallest) of the values
A more complex task is the problem of optimization (synthesis) of the system structure. If the structure of the system can be described quite completely by known functions with a finite number of parameters, then the problem comes down to optimizing these parameters. In the special case when the objective function and all functions that define the constraints linearly depend on the parameters, the problem is reduced to linear programming. In some
In some cases, it is possible to solve the problem analytically based on the methods of functional analysis.
In general, solving the SPI optimization problem may turn out to be complex and unsuitable for decision making. Therefore, they usually resort to a step-by-step optimization procedure. First, for example, optimization is carried out according to information parameters, and then - according to technical and economic indicators. At the first stage, a structural diagram of the system is determined, which allows one to evaluate its main potential characteristics, select modulation and coding methods, and a method of signal processing in the receiver. Then the operating algorithms and parameters of individual system blocks (modem, channel codec, source codec, etc.) are determined. The final stage is the design of the system.
Technical and economic analysis is based on at least two indicators: effect and costs. At the same time, the main principles for determining the effectiveness of SPI may be the principle of maximum effect or the principle of minimum costs
Costs are usually taken as the given annual costs per unit of production (in our case, the cost of transmitting one bit per second).
SPI optimization.
The useful effect (product) in SPI is the amount of information delivered to the consumer per unit of time (transmission speed) for a given transmission fidelity, i.e. the average transmission speed over a channel in a communication network with the probability of an error. This speed is usually called the system capacity and is denoted in contrast to the Shannon channel capacity C. If C is a theoretical concept that characterizes the limiting capabilities of the channel, that is, a technical characteristic that depends on real characteristics and equipment of this system.
By definition
Here is the number of bits of information transmitted over a channel in a communication network during the time where is the transmission time (duration) of the message; delay time, including waiting time; source codec efficiency, message (source) redundancy, channel efficiency calculated taking into account the correction code, type of modulation and losses in the channel, channel codec efficiency, - modulation efficiency, network efficiency.
Taking into account expressions (11.4) and (11.28) we have
where according to (11.23) and (11.24)
With; - this is the real amount of information that is delivered to the consumer per unit of time at a given transmission quality
When optimizing the SPI, expression (11.29) for can be taken as the objective function. Then the task will be to find a communication system that delivers the maximum of this function under given conditions and restrictions. Mathematically, this is a nonlinear and, in some cases, linear programming problem. In some special cases, the problem is solved analytically, as a problem of searching for the extremum of a functional. In cases where it is necessary to ensure a given sufficiently high value, the choice of system is carried out by analyzing (comparing) possible options that meet the specified requirements. The required value of C in these cases is achieved by a compromise choice of indicators included in expression (11.29), taking into account technical and economic requirements.
The problem of optimizing SPI arises both when developing new and improving existing systems. In many cases, it is posed as a task to increase the effectiveness of SPI. The solution to such a problem is not unambiguous. A high (or necessary) value of C according to (11.29) can be achieved in various ways.
Let's consider this using the example of a discrete message transmission system (SDTS). We will assume that the communication network in which the SPDS in question must operate is known (its efficiency is specified. The source of messages is usually also known (its redundancy is specified. The required fidelity (error) of transmission rpop is also specified.
The bandwidth of channel C is the information resource of the system. It is usually specified or selected based on existing standards. There are options here when choosing. According to Shannon's formula, the value is completely determined by the energy resource and frequency resource. The choice of channel frequency band is very limited and is regulated by international agreements. As for the energy resource, it depends on the power of the transmitter and the noise temperature of the receiver, and in radio systems, on the antenna gain O. where A is a constant coefficient. This implies the possibility of varying the values to obtain the required value of C. Thus, the use of highly directional antennas can significantly improve the channel energy for a given transmitter and receiver.
With the selected value of C and given values, increasing the efficiency of the SPI is reduced to increasing the efficiency of the channel. According to (11.4), information efficiency depends on the energy efficiency and specific speed y, which can be calculated using formulas (11.8) and (11.9). Then, for a given error probability and the calculated value of channel energy using exchange nomograms (Fig. 11.6), you can choose the type of modulation and coding method.
Alexey Ukolov - about what tricks mobile operators use and how small businesses can save on telephone calls
Mobile operators are constantly introducing new tariffs to the market. And understanding them can be quite difficult. Using the Tariffer service, subscribers can compare their current tariff with other offers on the market and choose the best option for themselves. If for individuals the benefit from switching to another tariff can amount to several hundred rubles per month, then the savings for large companies can amount to hundreds of thousands of rubles. The founder of the Tariffer service, Alexey Ukolov, told the website about what tricks cellular operators have and how to track communication costs in real time.
35 years old, entrepreneur from Samara, founder and CEO of the service "Tarifer"(selection of optimal cellular tariff plans). Education: International Market Institute (Faculty of Economics and Management). The Tariffer service was launched in 2007. In 2008, the service received the Best Soft award, and in 2009, the Microsoft Business Start award.
Looking for the best offer
The idea for the Tariffer service came from Alexey Ukolov’s brother, Dmitry, in 2007. At that time, he worked as a programmer in one of the Samara companies. By this time, Alexey himself had experience in various projects in the field of trade - not always successful. After discussing the idea, the brothers decided to make a trial version of the service, which would analyze the details of calls and select the most suitable tariff for a particular person.
“The idea was on the surface. Many people had problems choosing a tariff. At that moment the market was quite wild. Then there was a real leapfrog with tariffs. There were both per-minute and per-second rates. Some tariffs included some kind of packages. There was also a connection fee. In general, there were many nuances that needed to be taken into account and which were difficult for many people to understand,” says Alexey Ukolov.
In the new project, Dmitry took on programming, and Alexey took on all other issues. In 2008, another partner joined the project - Kirill Nasedkin. He had his own web design studio and took over the development of the site.
Creating a test version of the service took several months. And we spent several months creating the website. In 2008, a year and a half after work on the project began, the first version of Tarifer.ru was launched. And at the end of the same year, the site was redone, and came to a version similar to the current one.
The company has competitors in Russia, but they are few. They manually or semi-manually help clients analyze their costs and select a new tariff plan. “Our advantage over them is in technology, in this regard we are much stronger,” says Alexey Ukolov.
We live on our own
The founding fathers launched and developed their project exclusively with their own funds - they never attracted borrowed money. About a million rubles were spent on developing a website prototype. The service brought in its first revenue in 2009, and in 2010 “Tarifer” reached breakeven.
The growth of the project was facilitated by the victory in the Microsoft Business Start competition for Russian startups in 2009. For the victory, “Tarifer” received a grant of 1 million rubles. He allowed, among other things, to hire the first employees. A programmer and a technical support specialist came to the company to work with the tariff plan database.
The addition of new employees to the team accelerated the development of the service. At that time, the founders of the company decided to focus on the corporate market, as it was more promising for their type of activity. Towards the end of 2009, Tarifer acquired its first corporate clients.
Finding them was not difficult, since the company set a fairly low price for its corporate product - several thousand rubles, regardless of the size of the client company and the number of SIM cards being “calculated”. But it soon became clear to the founders of the project that with such a pricing policy it was simply unprofitable to work with large companies, and the price list was revised. Naturally, selling became more difficult, and in 2011 the company hired a sales manager. Previously, these functions were performed by Alexey Ukolov himself, and, as he himself admits, he did not always have enough time for this. With the arrival of the new manager, sales increased significantly.
"Tariff" for individuals
Private clients can independently choose the most favorable mobile communication tariff for themselves. The client must enter his phone number and password from the personal account of the mobile operator. If a person does not know this password, the program will help him “enter the account” - you just need to follow the instructions. The service “unloads” call details for the month and analyzes it. Based on the analysis, the most favorable tariffs are recommended to the client - both from “our own” and “foreign” operators.
The database of tariff plans is supplemented and updated daily. It includes both federal and all regional tariffs of the “Big Four” operators: Beeline, MTS, Megafon and Tele2.
“Operators are constantly introducing new tariffs. And we regularly make improvements to the calculation algorithm, changing something all the time. Now the main trend is the transition to package tariffs. In addition to telephone communications, they include the use of the Internet under certain conditions. And we have “sharpened” all our tools to work effectively with package tariffs,” says Alexey.
Corporate program
Corporate clients of Tarifer can choose one of two programs for using the service. The first is cost analysis. The program determines in which areas communication costs are higher than the company average. A company's telephone costs are broken down by employee, department, and cost source.
The second program is directly optimizing costs, that is, selecting the most favorable tariffs. The program analyzes all client numbers and selects the most advantageous offer for each number.
When working with companies, Tarifer uses two schemes. The company can purchase the necessary software from Tarifer and then do everything independently. A company employee working with this program will have to upload call details into it, build reports and select tariff plans. For example, this option is used if corporate security rules do not allow transferring data to third parties.
But the most convenient cooperation option for corporate clients is to delegate all functions of analyzing communication costs and selecting tariffs to the Tariffer service. In this case, the client simply sends all the bills for communication, and then the company’s specialists work with them.
The program can also work with individual tariff plans, which many corporate clients have. These tariffs are “non-public”, that is, they are not presented on the operator’s websites. The customer provides a description of their pricing plan, and the terms of that plan are added to that specific client's program. The customer can see this option in his program and use it in calculations.
One of the main difficulties when working with corporations is the need to download call details from the personal account of your telecom operator. Tarifer specialists are now working to automatically collect all data from operators’ personal accounts. Then the client will only need to provide his login and password for his personal account on the operator’s website.
Online monitoring
Until recently, tariff selection schemes were aimed at analyzing communication costs that had already taken place over the past month. But in the near future, Tarifer is launching another technology for corporate clients - monitoring. It allows the client to track and adjust costs in real time.
The new technology allows you to see how much employees have spent on mobile communications and the Internet in the current month up to this minute, and how much they are currently spending. If the program “notices” that communication costs have increased sharply, it sends an SMS alert to the client.
The service is needed primarily to prevent unplanned communication costs, especially in roaming. For example, a person forgot to turn off the Internet. In roaming, the subscriber may even practically not use the Internet or communications. But thanks to rounding rules and certain operator tricks, he will receive an unexpectedly large bill at the end of the month. And since the company has a common balance for all numbers, this may be discovered late. And the communication bill will be an unpleasant surprise for the company.
It is not always possible to shift these costs to the employee for legal reasons. Therefore, companies often end up with hundreds of thousands of rubles due to the fact that someone forgot to turn off the Internet while roaming or used some services incorrectly.
“The director of the company that we are currently servicing under our monitoring program has gone abroad. And there I used the Internet, after which a bill for 160,000 rubles came to this number. The company is not very large, and this amount is significant for them. Unfortunately, at that time this client did not have a monitoring program connected. And they did not understand where such a sum for communication came from. Now they can see in real time the reason for increased costs and prevent them in time,” Alexey gives an example.
Data on sharply increased expenses enters the Tarifera system 15 minutes after the client begins to overspend. It takes about 10 more minutes to react to the situation and inform the client about it. A message about expenses can be sent to both the embezzler himself and his company. This way, the customer can see and stop unscheduled communication charges within half an hour after they started.
The service began working in test mode two months ago. Currently, Tarifer serves about 50 companies under this program, and the first reviews of the service are the most positive.
Clients
Tarifer considers companies with 30 or more employees as corporate clients. If the company has no more than 15-20 numbers, then all calculations can be done manually in a few hours. With a number of 30 numbers or more, the volume of data is already quite serious. And the company already needs to make a decision: either it allocates a specialist to work with them, or attracts an “outside” contractor.
In total, Tarifer has about 400 corporate users. Each company has from 50 to 5000 people. Of the top 10 largest Russian companies, four use Tarifera services.
The number of private clients who have used the service since its foundation is about two hundred thousand people. Now the service website receives about 200-300 orders per day from individuals.
If we are talking about an average company of 100 people spending 500 rubles per month on one telephone number, then its savings after calculating the “Tariff” can amount to about 10-15 thousand rubles per month.
But the amount of savings largely depends on the structure and type of activity of the company. If this is a trading company whose representatives spend a lot of time in the regions and use roaming, then their communication costs are many times higher. And then her savings from working with Tarifera solutions are several times greater than those of other companies.
Tarifer employees periodically call their clients to find out their opinions about the service. “I myself from time to time take a random list of clients, call and ask them what can be improved and corrected in the service. In particular, thanks to such communication, we now have a “real-time monitoring” service,” says Alexey Ukolov.
Prices for services
For individuals, the service has been free for a long time. But now a fee has been introduced for the service - and anyone can calculate the optimal tariff for 140 rubles. The website has a tariff plan calculator into which you can enter all the parameters of your communication use. The average savings for private clients after using the service and switching to a new tariff is 37%.
Payment occurs after all calculations and report preparation. However, if during the calculation it turns out that the client’s current tariff is the most profitable, Tariffer does not charge him and all analytics are provided to the client as a bonus.
Users who are well versed in the variety of tariff plans can choose a tariff for themselves for free. The website contains publicly available a complete database of all current offers from the Big Four operators (including regional tariffs).
The cost of servicing companies depends on the number of their employees and the required functionality. The price varies from 10 to 20 rubles per month for each company SIM card, depending on the services included in the service (just cost analysis or analysis + selection of new tariff plans).
"Pitfalls"
Any business built on working with the corporate sector faces the problem of coordination within client companies. In large structures, the decision-making system is usually multi-stage. It happens that negotiations with some large companies drag on for up to several years.
In addition, not all companies have an urgent need for “tariff” savings. For many companies, communication costs are a small expense item compared to the overall budget. And many managers simply do not want to spend time seriously studying the issue of corporate tariffs.
But even in those companies where the issue of reducing communication costs is acute, not everyone is happy with Tariffer’s offers. The employee responsible for corporate mobile communications is not always interested in saving the company money. Therefore, the task of Tarifer managers is, whenever possible, to contact top officials of companies interested in saving.
Some existing Tarifer clients almost never use the tariff selection function. It is important for them that corporate communications data is organized. And the service helps them store information about all calls made from corporate numbers. Among these clients there are many branches of Western corporations.
Operator Tricks
Tarifer strives for its customers to pay less for communications. The task of mobile operators is exactly the opposite - to increase fees from customers. To achieve this, the Big Four have many tricks and tricks, one of the main ones being “archive tariff plans”.
The meaning of the trick is quite simple. The client chooses a tariff plan, connects and uses it. After some time, the cellular company sends this plan “to the archive.” Moreover, the operator may still have a current tariff with exactly the same name. For example, three years ago the client connected to the “July” tariff. Now the operator has a tariff with exactly the same name, but with different conditions. And the tariff, which the client has been using for 3 years, has long been archived, and now it is called “July-2013”.
The benefit for the operator is that the “archive” tariff is usually made more expensive than the current tariff plan. In any subscription service agreement it is written that the operator has the right to change the terms of the tariff without informing the client about it. The subscriber can see among the operator company's offers a tariff with the same name as his own. But in fact, this is no longer his tariff, and he is served on the archived version, which is most likely less profitable.
“We just recently dealt with such a case. The client said that we recommended his own tariff, and at the same time promised savings. We began to look into it, and it turned out that he was on the archived version of the same tariff, which included a much smaller package of services. There are not enough services there - and the client overpays a lot of money, because the tariff is actually not the same. So if a subscriber has been served on the same tariff for several years, it makes sense for him to check if there is now a more profitable option,” recommends Alexey.
When a new operator enters the market, it often attracts users with low prices. At the same time, other operators are forced to adapt, reduce prices, and thus the situation in the cellular communications market is changing. But, having gained a foothold in the market, newcomers usually begin to gradually raise prices, and the overall market situation returns to its original state.
Now the strategy of operators entering new markets can be seen in the example of Tele2. Around the moment when this operator began to conquer Moscow with low tariffs, prices in the regions began to rise.
“Another feature of Tele2 is that they actually have low “front-end” tariffs, that is, numbers that the client pays attention to. But for various kinds of “additional services” (long-distance, roaming, etc.), their prices are far from the most favorable,” Alexey reveals his secrets.
Promotion
Since Tarifer has two different audiences - private and corporate, there are also two websites. Services for individuals are posted - a tariff calculator and the all-Russian tariff base. A is the main website of the project, which contains both corporate solutions and links to tarifer.net.
Over time, tarifer.ru will become a site only for corporate users, and tarifer.net - for private users. The website tarifer.ru is currently under redesign. Its new version is scheduled to launch at the end of August.
The founders of Tarifer chose direct sales as the main way to promote their services. Managers contact potential clients through cold calling. The company has a “two-level” sales department. “First-level” managers work like a call center. Their task is to call and initially communicate with the client. If the client shows interest, he is transferred to a more professional sales manager.
Team
In total, the Tarifer company employs about 30 people. The “head” office and developers are located in Samara, and the company has a sales office in Moscow. 10 people make up the sales department, the rest are developers, administrative staff and technical support staff.
Technical support receives calls and requests from customers. In addition, she has a large scope of work related to data updating. This includes support and replenishment of the database of tariff plans, support of the database of telephone numbers and recognition of all billing detail formats that are only possible with operators.
Despite the impressive work experience, the project has not yet acquired its own mobile application. It is planned to be made in two versions: for individuals and for corporate clients.
The most current plan for the coming months is the further development of the monitoring service (tracking and adjusting expenses in real time). While it can be used in a test version, its “commercial” launch will begin in the fall.
“We are planning a serious development of this service so that it also tracks the balances of current service packages. Gradually, we will reduce all our services to one interface, everything will be built on the basis of monitoring,” sums up Alexey Ukolov.
